Electrical transformers are vital components found virtually in most power-operated equipments. T... more Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inherent in transformers rises above allowable threshold a reduction in efficiency of operation occurs. In addition, this could cause other components in the system to malfunction. The aim of this work is to detect the remote causes of this undesirable thermal rise in transformers such as oil distribution transformers and ways to control this prevailing thermal problem. Oil transformers consist of these components: windings usually made of copper or aluminum conductor, the core normally made of silicon steel, the heat radiators, and the dielectric materials such as transformer oil, cellulose insulators and other peripherals. The Resistor-Inductor-Capacitor Thermal Network (RLCTN) model at architectural level identifies with these components to have ensemble operational mode as oil transformer. The Inductor represents the windings, the Resistor representing the core and the Capacitor represents the dielectrics. Thermography of transformer under various loading conditions was analyzed base on Infrared thermal gradient. Mathematical, experimental, and simulation results gotten through RLCTN with respect to time and thermal image analysis proved that the capacitance of the dielectric is inversely proportional to the thermal rise.
2013 IEEE 3rd International Conference on System Engineering and Technology, 2013
This paper presents a non-parametric method to produce stress index using Electroencephalogram (E... more This paper presents a non-parametric method to produce stress index using Electroencephalogram (EEG) signals. 180 EEG datasets from healthy subjects were evaluated at two cognitive states; resting state (Eyes Closed) and working state (Eyes Open). In working cognitive state, subjects were asked to answer the Intelligence Quotient (IQ) test questions. The EEG datasets were categorized into 4 groups. Energy Spectral Density (ESD) ratios and Spectral Centroids (SC) from the two tasks were calculated and selected as input features to k-Nearest Neighbor (k-NN) classifier. Shannon's Entropy (SE) was used to detect and quantify the distribution of ESD due to stressors (stress factors). The stress indexes were assigned based on the results of classification, ESD ratios, SC and SE. There were 3 types of stress indexes can be assigned which represent the stress level (low stress, moderate stress and high stress) at classification accuracy of 88.89%. The regression coefficient of the SC of Beta and Alpha was 77%.
Abstract Electrical and Electronic objects, which have a temperature of operating condition above... more Abstract Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical ...
According to the U.S. National Highway Traffic Safety Administration, single vehicle road departu... more According to the U.S. National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year[1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, Probabilistic Hough Transform (PHT) is presented in this paper for intelligent Lane markers recognition which use a fixed camera installed on the vehicle to transmit video information. The result of experiment proved that under inconsistent illumination and a diversity of road conditions, the accuracy and efficiency of developed system have been improved greatly.
According to the U.S. National Highway Traffic Safety Administration, single vehicle road departu... more According to the U.S. National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year[1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, Probabilistic Hough Transform (PHT) is presented in this paper for intelligent Lane markers recognition which use a fixed camera installed on the vehicle to transmit video information. The result of experiment proved that under inconsistent illumination and a diversity of road conditions, the accuracy and efficiency of developed system have been improved greatly.
It is very challenging to recognize a face from an image due to the wide variety of face and the ... more It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection framework that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space and HSV color space. Firstly, we build a skin Gaussian model in Cg-Cr color space, and then some constraints are used to get candidates of face. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions..
Social Force Model (SFM) is commonly used in crowd analysis. In this paper, modified SFM is propo... more Social Force Model (SFM) is commonly used in crowd analysis. In this paper, modified SFM is proposed to detect and localize the abnormality in crowd scene. This task is done by estimating the interaction forces in image frames based on SFM theory. The algorithm is jointly used with optical flow, which provides flow vector to be used in particle advection. The moving particles are treated as a main cue instead of particle tracking. Some modifications of SFM algorithm has been proposed here in order to capture the particles which carry significant information of the crowd. The interaction forces are being selected based on Fisher's equation. The computed interaction forces determine the synergy between the advected particles, whereby high magnitude of interaction force has high possibility of abnormal behaviour happened.
In this study, an approach of extraction analysis for bearing fault diagnosis of rotating machine... more In this study, an approach of extraction analysis for bearing fault diagnosis of rotating machinery based on thermogram investigation using color features is proposed in this paper. This research was proposed since condition monitoring and motor failures are great concern in industries. Early fault detection in machineries can avoid production lost and reducing maintenance costs. Therefore, in this work, infrared thermography (IRT) is used as a tool to detect early sign for bearing fault since this infrared thermography (IRT) is one of the most effective non-destructive testing techniques of condition monitoring and fault diagnostics. By using this infrared thermography (IRT) technology, the information of machine condition can be analyzed. In the present study, 300 thermal images are used in this simulation process whereby the images are classified into two classes namely normal and abnormal. The first class consists of 150 images normal bearing while another 150 images denote abnormal bearing class. SURF feature-based algorithm, RGB color space and active contour segmentation are employed in this paper in order to process and differentiate between normal and abnormal bearing image by means of color features called statistical technique. The experiment results indicate that this statistical features of RGB color space able to distinguish the differences between normal and abnormal features of bearing in machinery system.
Inspired by the estimation capability of Kalman filter, we have recently introduced a novel popul... more Inspired by the estimation capability of Kalman filter, we have recently introduced a novel population-based optimization algorithm called simulated Kalman filter (SKF). Every agent in SKF is regarded as a Kalman filter. Based on the mechanism of Kalman filtering, which includes prediction, measurement, and estimation, the global minimum/maximum can be estimated. Measurement process, which is required in Kalman filtering, is mathematically modelled and simulated. Agents communicate among them to update and improve the solution during the search process. Inspired by the bird flocking, particle swarm optimization (PSO) has been introduced in 1994. In PSO, a swarm of agent search the global minimum/maximum by velocity and position updates, which are influenced by current position of agent, current position of agent, personal best, and global best of the swarm. In this research, SKF and PSO are hybridized in such a way that PSO is employed as prediction operator in SKF. The performance of the proposed hybrid SKF-PSO algorithm (SKF-PSO) is compared against SKF and PSO using CEC2014 benchmark dataset for continuous numerical optimization problems. Based on the analysis of experimental results, we found that the proposed hybrid SKF-PSO is superior to both SKF and PSO algorithm.
— Machine vision is an application of computer vision to automate conventional work in industry, ... more — Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.
Abstract—Viral outbreaks such as SARS, H5N1, and H1N1
have led the need of temperature monitoring... more Abstract—Viral outbreaks such as SARS, H5N1, and H1N1 have led the need of temperature monitoring in areas where crowds are expected such as in hospitals and airports. Infrared (IR) thermal screening, hitherto, has been found as powerful, quick and non-invasive method to detect the elevated temperature of febrile individuals when the temperature of the face is above 36°. Past research has proved that the most excellent area that represents the core body temperature is the medial canthal areas of the face as it is less dependent on the effects of ambient temperature. In realistic situation, the moving subjects are random and the angles of the skin surface and distances change dynamically and misdetection of canthal area could also be due to any other unwanted objects that have the same temperature. The normal approach is to ask a single person to stand still for 2 seconds to capture the temperature. However this approach is ineffective and this will lead to long queue in public. To solve this issue, we have proposed a combination of physiology-based and optical flow algorithm to extract vascular network from the face. The thermal camera is provided with colour and audible alarming, hence when the camera detect an abnormal temperature from a person, automatic febrile individual tracking alarm will report to the operator the current location of the individual.
Diseases caused by intestinal parasite are alarming especially caused by Ascaris Lumbricoides. An... more Diseases caused by intestinal parasite are alarming especially caused by Ascaris Lumbricoides. An efficient technique to detect existence of parasite automatically in fecal sample is vital. Therefore, this research is focus on detecting Ascaris Lumbricoides in fecal sample images by using digital image processing technique. There are four novel steps proposed in the detection process which are boundary detection, midpoint determination, radius distance calculation and parasite detection. The results generated are 100% precision and recall of 73%. This proves that this technique is a success.
The most widely used method for weed control is to use agricultural chemicals (herbicides product... more The most widely used method for weed control is to use agricultural chemicals (herbicides products). This heavy reliance on chemicals raises many environmental and economic concerns, causing many plantation companies to seek alternatives for weed control in order to reduce chemical usage in their plantation. Since manual labor is costly and expensive, an automated weed control system may be economically feasible. A machine vision precision automated weed control system could also reduce the usage of chemicals. In this research, an intelligent real-time system for automatic weeding strategy in oil palm plantation using image processing has been developed to identify and discriminate the weed types namely as narrow and broad. In machine vision technology, the main component of the system is image processing to recognize type of weeds. Three techniques of image processing, involving statistical approach GLCM and structural approach FFT and SIFT, have been used and compared to find the best solution of weed recognition for classification. The developed machine vision system consists of a mechanical structure, which includes a sprayer, a Logitech web digital camera, 12v motor coupled with a pump system and a small size CPU as a processor. Offline images and recorded video has been tested to the system and classification result of weed shows the successful rate is above 80%.
Global positioning system (GPS) is being actively employed in a variety of vehicular monitoring s... more Global positioning system (GPS) is being actively employed in a variety of vehicular monitoring systems such as automated car navigation, emergency assistance, fleet management and automotive assistance. Nowadays easily observed many passengers footed at the Bus stations waiting for their desired bus. This paper considers performance issues in Public transport monitoring system that utilize GPS and embedded RF radio chip. For the purpose, a new intelligent Multi ID buses movement monitoring and station reporting system comprising of GPS, in collaboration with succession of sophisticated Transceivers modules, is presented here. In addition to some fundamental functions such as real-time monitoring, some featured functions are combined to make the system compatible with the daily operations of any public transport scheme. Because of performance and cost constraints, this monitoring system is carefully designed to balance system partitioning and resource sharing. The proposed method will surely provide smooth and linear transmission of location information to the bus stations which led people to take decision either to wait for Bus or not.
feature extraction tool to analyze sub-band frequency of Abstract--The purpose of feature extract... more feature extraction tool to analyze sub-band frequency of Abstract--The purpose of feature extraction technique in wavelet transform. The sub-band frequencies were used as an image processing is to represent the image in its compact and input to the expert model network. The common technique unique form of single values or matrix vector. Low level feature used for feature extraction of DWT coefficient is by using extraction involves automatic extraction of features from an neural network [6], [7], [8]. In this study, wavelets will be image without doing any processing method. In this paper, we used in the analysis of narrow and broad weed images since consider the use of high level feature extraction technique to the harcteisti ofnarow nd boadwee by DWT allows decomposition of the image into different levels investigate theof resolution. By doing so, we introduce a new feature set that implementing the 2 Dimensional Discrete Wavelet Transform is reduon Bysis of we oducen t. sehat Pahang,
The paper presents switching techniques for pulse-width-modulated-based z-source inverter; simple... more The paper presents switching techniques for pulse-width-modulated-based z-source inverter; simple boost PWM, maximum boost PWM, maximum constant boost PWM, modified-reference PWM, modified space vector PWM, hysteresis current control, and sine carrier PWM. Concepts and ideas behind the techniques are briefly explained. An overall view is summed up of the PWM controls, in terms of their achievements and system involvement in ZSI.
Ordinary CCTV can only be used to record incidents if it occur. It works without preventing it an... more Ordinary CCTV can only be used to record incidents if it occur. It works without preventing it and it is only useful to be an evidence for the investigation. The purpose of developing this project is as the earlier prevention to avoid crime by giving alert or feedback from the object that was detected from captured video. The captured video in this project will be convert into frame of images and being analyze by using MATLAB software that already consist all the techniques of image processing. The output of this project will be classified if there is any motion or not by using the value of total sum of pixel value from each image data. The classification is actually based on the threshold value. This project indirectly reduce weakness and careless of human guard observation as it give continuous 24-hour monitoring of surveillance video to alert security officers to an intruder potential.
Abstract In machine vision application, the main part to analyze an image is to identify its feat... more Abstract In machine vision application, the main part to analyze an image is to identify its features which contribute to efficiency of the system. Many applications in vision system and image analysis used face detection as a feature of their whole system development. In application such as video surveillance, fatigue detection and security system, face is a fundamental step in the analysis before proceed to system implementation. It is very challenging to recognize a face from an image due to the wide variety of face and the ...
Electrical transformers are vital components found virtually in most power-operated equipments. T... more Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inherent in transformers rises above allowable threshold a reduction in efficiency of operation occurs. In addition, this could cause other components in the system to malfunction. The aim of this work is to detect the remote causes of this undesirable thermal rise in transformers such as oil distribution transformers and ways to control this prevailing thermal problem. Oil transformers consist of these components: windings usually made of copper or aluminum conductor, the core normally made of silicon steel, the heat radiators, and the dielectric materials such as transformer oil, cellulose insulators and other peripherals. The Resistor-Inductor-Capacitor Thermal Network (RLCTN) model at architectural level identifies with these components to have ensemble operational mode as oil transformer. The Inductor represents the windings, the Resistor representing the core and the Capacitor represents the dielectrics. Thermography of transformer under various loading conditions was analyzed base on Infrared thermal gradient. Mathematical, experimental, and simulation results gotten through RLCTN with respect to time and thermal image analysis proved that the capacitance of the dielectric is inversely proportional to the thermal rise.
2013 IEEE 3rd International Conference on System Engineering and Technology, 2013
This paper presents a non-parametric method to produce stress index using Electroencephalogram (E... more This paper presents a non-parametric method to produce stress index using Electroencephalogram (EEG) signals. 180 EEG datasets from healthy subjects were evaluated at two cognitive states; resting state (Eyes Closed) and working state (Eyes Open). In working cognitive state, subjects were asked to answer the Intelligence Quotient (IQ) test questions. The EEG datasets were categorized into 4 groups. Energy Spectral Density (ESD) ratios and Spectral Centroids (SC) from the two tasks were calculated and selected as input features to k-Nearest Neighbor (k-NN) classifier. Shannon's Entropy (SE) was used to detect and quantify the distribution of ESD due to stressors (stress factors). The stress indexes were assigned based on the results of classification, ESD ratios, SC and SE. There were 3 types of stress indexes can be assigned which represent the stress level (low stress, moderate stress and high stress) at classification accuracy of 88.89%. The regression coefficient of the SC of Beta and Alpha was 77%.
Abstract Electrical and Electronic objects, which have a temperature of operating condition above... more Abstract Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical ...
According to the U.S. National Highway Traffic Safety Administration, single vehicle road departu... more According to the U.S. National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year[1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, Probabilistic Hough Transform (PHT) is presented in this paper for intelligent Lane markers recognition which use a fixed camera installed on the vehicle to transmit video information. The result of experiment proved that under inconsistent illumination and a diversity of road conditions, the accuracy and efficiency of developed system have been improved greatly.
According to the U.S. National Highway Traffic Safety Administration, single vehicle road departu... more According to the U.S. National Highway Traffic Safety Administration, single vehicle road departures result in many serious accidents each year[1]. An intelligent lane markers recognition and localization system can assist vehicles stay in proper location of a lane that will reduce possibility of car accidents correspondingly. A great deal of lane recognition algorithms have been developed over the past several decades. However, reliable detection is still an issue because of variable road face conditions. An optimum algorithm, Probabilistic Hough Transform (PHT) is presented in this paper for intelligent Lane markers recognition which use a fixed camera installed on the vehicle to transmit video information. The result of experiment proved that under inconsistent illumination and a diversity of road conditions, the accuracy and efficiency of developed system have been improved greatly.
It is very challenging to recognize a face from an image due to the wide variety of face and the ... more It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection framework that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space and HSV color space. Firstly, we build a skin Gaussian model in Cg-Cr color space, and then some constraints are used to get candidates of face. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions..
Social Force Model (SFM) is commonly used in crowd analysis. In this paper, modified SFM is propo... more Social Force Model (SFM) is commonly used in crowd analysis. In this paper, modified SFM is proposed to detect and localize the abnormality in crowd scene. This task is done by estimating the interaction forces in image frames based on SFM theory. The algorithm is jointly used with optical flow, which provides flow vector to be used in particle advection. The moving particles are treated as a main cue instead of particle tracking. Some modifications of SFM algorithm has been proposed here in order to capture the particles which carry significant information of the crowd. The interaction forces are being selected based on Fisher's equation. The computed interaction forces determine the synergy between the advected particles, whereby high magnitude of interaction force has high possibility of abnormal behaviour happened.
In this study, an approach of extraction analysis for bearing fault diagnosis of rotating machine... more In this study, an approach of extraction analysis for bearing fault diagnosis of rotating machinery based on thermogram investigation using color features is proposed in this paper. This research was proposed since condition monitoring and motor failures are great concern in industries. Early fault detection in machineries can avoid production lost and reducing maintenance costs. Therefore, in this work, infrared thermography (IRT) is used as a tool to detect early sign for bearing fault since this infrared thermography (IRT) is one of the most effective non-destructive testing techniques of condition monitoring and fault diagnostics. By using this infrared thermography (IRT) technology, the information of machine condition can be analyzed. In the present study, 300 thermal images are used in this simulation process whereby the images are classified into two classes namely normal and abnormal. The first class consists of 150 images normal bearing while another 150 images denote abnormal bearing class. SURF feature-based algorithm, RGB color space and active contour segmentation are employed in this paper in order to process and differentiate between normal and abnormal bearing image by means of color features called statistical technique. The experiment results indicate that this statistical features of RGB color space able to distinguish the differences between normal and abnormal features of bearing in machinery system.
Inspired by the estimation capability of Kalman filter, we have recently introduced a novel popul... more Inspired by the estimation capability of Kalman filter, we have recently introduced a novel population-based optimization algorithm called simulated Kalman filter (SKF). Every agent in SKF is regarded as a Kalman filter. Based on the mechanism of Kalman filtering, which includes prediction, measurement, and estimation, the global minimum/maximum can be estimated. Measurement process, which is required in Kalman filtering, is mathematically modelled and simulated. Agents communicate among them to update and improve the solution during the search process. Inspired by the bird flocking, particle swarm optimization (PSO) has been introduced in 1994. In PSO, a swarm of agent search the global minimum/maximum by velocity and position updates, which are influenced by current position of agent, current position of agent, personal best, and global best of the swarm. In this research, SKF and PSO are hybridized in such a way that PSO is employed as prediction operator in SKF. The performance of the proposed hybrid SKF-PSO algorithm (SKF-PSO) is compared against SKF and PSO using CEC2014 benchmark dataset for continuous numerical optimization problems. Based on the analysis of experimental results, we found that the proposed hybrid SKF-PSO is superior to both SKF and PSO algorithm.
— Machine vision is an application of computer vision to automate conventional work in industry, ... more — Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.
Abstract—Viral outbreaks such as SARS, H5N1, and H1N1
have led the need of temperature monitoring... more Abstract—Viral outbreaks such as SARS, H5N1, and H1N1 have led the need of temperature monitoring in areas where crowds are expected such as in hospitals and airports. Infrared (IR) thermal screening, hitherto, has been found as powerful, quick and non-invasive method to detect the elevated temperature of febrile individuals when the temperature of the face is above 36°. Past research has proved that the most excellent area that represents the core body temperature is the medial canthal areas of the face as it is less dependent on the effects of ambient temperature. In realistic situation, the moving subjects are random and the angles of the skin surface and distances change dynamically and misdetection of canthal area could also be due to any other unwanted objects that have the same temperature. The normal approach is to ask a single person to stand still for 2 seconds to capture the temperature. However this approach is ineffective and this will lead to long queue in public. To solve this issue, we have proposed a combination of physiology-based and optical flow algorithm to extract vascular network from the face. The thermal camera is provided with colour and audible alarming, hence when the camera detect an abnormal temperature from a person, automatic febrile individual tracking alarm will report to the operator the current location of the individual.
Diseases caused by intestinal parasite are alarming especially caused by Ascaris Lumbricoides. An... more Diseases caused by intestinal parasite are alarming especially caused by Ascaris Lumbricoides. An efficient technique to detect existence of parasite automatically in fecal sample is vital. Therefore, this research is focus on detecting Ascaris Lumbricoides in fecal sample images by using digital image processing technique. There are four novel steps proposed in the detection process which are boundary detection, midpoint determination, radius distance calculation and parasite detection. The results generated are 100% precision and recall of 73%. This proves that this technique is a success.
The most widely used method for weed control is to use agricultural chemicals (herbicides product... more The most widely used method for weed control is to use agricultural chemicals (herbicides products). This heavy reliance on chemicals raises many environmental and economic concerns, causing many plantation companies to seek alternatives for weed control in order to reduce chemical usage in their plantation. Since manual labor is costly and expensive, an automated weed control system may be economically feasible. A machine vision precision automated weed control system could also reduce the usage of chemicals. In this research, an intelligent real-time system for automatic weeding strategy in oil palm plantation using image processing has been developed to identify and discriminate the weed types namely as narrow and broad. In machine vision technology, the main component of the system is image processing to recognize type of weeds. Three techniques of image processing, involving statistical approach GLCM and structural approach FFT and SIFT, have been used and compared to find the best solution of weed recognition for classification. The developed machine vision system consists of a mechanical structure, which includes a sprayer, a Logitech web digital camera, 12v motor coupled with a pump system and a small size CPU as a processor. Offline images and recorded video has been tested to the system and classification result of weed shows the successful rate is above 80%.
Global positioning system (GPS) is being actively employed in a variety of vehicular monitoring s... more Global positioning system (GPS) is being actively employed in a variety of vehicular monitoring systems such as automated car navigation, emergency assistance, fleet management and automotive assistance. Nowadays easily observed many passengers footed at the Bus stations waiting for their desired bus. This paper considers performance issues in Public transport monitoring system that utilize GPS and embedded RF radio chip. For the purpose, a new intelligent Multi ID buses movement monitoring and station reporting system comprising of GPS, in collaboration with succession of sophisticated Transceivers modules, is presented here. In addition to some fundamental functions such as real-time monitoring, some featured functions are combined to make the system compatible with the daily operations of any public transport scheme. Because of performance and cost constraints, this monitoring system is carefully designed to balance system partitioning and resource sharing. The proposed method will surely provide smooth and linear transmission of location information to the bus stations which led people to take decision either to wait for Bus or not.
feature extraction tool to analyze sub-band frequency of Abstract--The purpose of feature extract... more feature extraction tool to analyze sub-band frequency of Abstract--The purpose of feature extraction technique in wavelet transform. The sub-band frequencies were used as an image processing is to represent the image in its compact and input to the expert model network. The common technique unique form of single values or matrix vector. Low level feature used for feature extraction of DWT coefficient is by using extraction involves automatic extraction of features from an neural network [6], [7], [8]. In this study, wavelets will be image without doing any processing method. In this paper, we used in the analysis of narrow and broad weed images since consider the use of high level feature extraction technique to the harcteisti ofnarow nd boadwee by DWT allows decomposition of the image into different levels investigate theof resolution. By doing so, we introduce a new feature set that implementing the 2 Dimensional Discrete Wavelet Transform is reduon Bysis of we oducen t. sehat Pahang,
The paper presents switching techniques for pulse-width-modulated-based z-source inverter; simple... more The paper presents switching techniques for pulse-width-modulated-based z-source inverter; simple boost PWM, maximum boost PWM, maximum constant boost PWM, modified-reference PWM, modified space vector PWM, hysteresis current control, and sine carrier PWM. Concepts and ideas behind the techniques are briefly explained. An overall view is summed up of the PWM controls, in terms of their achievements and system involvement in ZSI.
Ordinary CCTV can only be used to record incidents if it occur. It works without preventing it an... more Ordinary CCTV can only be used to record incidents if it occur. It works without preventing it and it is only useful to be an evidence for the investigation. The purpose of developing this project is as the earlier prevention to avoid crime by giving alert or feedback from the object that was detected from captured video. The captured video in this project will be convert into frame of images and being analyze by using MATLAB software that already consist all the techniques of image processing. The output of this project will be classified if there is any motion or not by using the value of total sum of pixel value from each image data. The classification is actually based on the threshold value. This project indirectly reduce weakness and careless of human guard observation as it give continuous 24-hour monitoring of surveillance video to alert security officers to an intruder potential.
Abstract In machine vision application, the main part to analyze an image is to identify its feat... more Abstract In machine vision application, the main part to analyze an image is to identify its features which contribute to efficiency of the system. Many applications in vision system and image analysis used face detection as a feature of their whole system development. In application such as video surveillance, fatigue detection and security system, face is a fundamental step in the analysis before proceed to system implementation. It is very challenging to recognize a face from an image due to the wide variety of face and the ...
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Papers by Kamarul Hawari
have led the need of temperature monitoring in areas where
crowds are expected such as in hospitals and airports. Infrared
(IR) thermal screening, hitherto, has been found as powerful,
quick and non-invasive method to detect the elevated
temperature of febrile individuals when the temperature of the
face is above 36°. Past research has proved that the most
excellent area that represents the core body temperature is the
medial canthal areas of the face as it is less dependent on the
effects of ambient temperature. In realistic situation, the moving
subjects are random and the angles of the skin surface and
distances change dynamically and misdetection of canthal area
could also be due to any other unwanted objects that have the
same temperature. The normal approach is to ask a single
person to stand still for 2 seconds to capture the temperature.
However this approach is ineffective and this will lead to long
queue in public. To solve this issue, we have proposed a
combination of physiology-based and optical flow algorithm to
extract vascular network from the face. The thermal camera is
provided with colour and audible alarming, hence when the
camera detect an abnormal temperature from a person,
automatic febrile individual tracking alarm will report to the
operator the current location of the individual.
have led the need of temperature monitoring in areas where
crowds are expected such as in hospitals and airports. Infrared
(IR) thermal screening, hitherto, has been found as powerful,
quick and non-invasive method to detect the elevated
temperature of febrile individuals when the temperature of the
face is above 36°. Past research has proved that the most
excellent area that represents the core body temperature is the
medial canthal areas of the face as it is less dependent on the
effects of ambient temperature. In realistic situation, the moving
subjects are random and the angles of the skin surface and
distances change dynamically and misdetection of canthal area
could also be due to any other unwanted objects that have the
same temperature. The normal approach is to ask a single
person to stand still for 2 seconds to capture the temperature.
However this approach is ineffective and this will lead to long
queue in public. To solve this issue, we have proposed a
combination of physiology-based and optical flow algorithm to
extract vascular network from the face. The thermal camera is
provided with colour and audible alarming, hence when the
camera detect an abnormal temperature from a person,
automatic febrile individual tracking alarm will report to the
operator the current location of the individual.