Papers by Dr.P.G.Krishna Mohan
Sadhana, 2008
Applications of power operational amplifiers (opamps) are increasing day by day in the industry a... more Applications of power operational amplifiers (opamps) are increasing day by day in the industry as they are used in audio amplifiers, Piezo transducer systems and the electron deflection systems. Power operational amplifiers have all the features of a general purpose opamp except the additional power handling capability. The power handling feature can be achieved using an external circuitry around a regular opamp. Normally power opamps can deliver current more than 50 mA and can operate on the supply voltage more than ±25 V. This paper gives the details of one of the power opamps developed to drive the Piezo Actuators for Active Vibration Control (AVC) of aircraft/aerospace structures. The designed power opamp will work on ±200 V supply voltage and can deliver 200 mA current.
2014 4th International Conference on Image Processing Theory, Tools and Applications (IPTA), 2014
In general, this paper deals with Image Processing using Metaheuristics Optimization Algorithms (... more In general, this paper deals with Image Processing using Metaheuristics Optimization Algorithms (IP-MOA). We are focused on supervised classification of remotely sensed images using a clonal selection theory of an Artificial Immune System (AIS). We shall propose a comparative study between the maximum likelihood (MLLH) classifier which is statistical and probabilistic approach and artificial immune system (AIS) which is a bio-inspired approach and commonly named “metaheuristcs”. The most motivations to explore this new kind of approaches for data classification are also presented. MLLH and AIS are applied to classify a multispectral image acquired on June 2001 by ETM+ sensor of Landsat-7 satellite. This multi-band image covers a northeastern part of Algiers (Algeria). From obtained results, we concluded that AIS approach may present a promising metaheuristic classifier for data classification. Keywords—Remote sensing image, classification, metaheuristics optimization algorithms, clonal selection, artificial immune system.
A novel feature descriptor called local tri directional median differential excitation cooccurren... more A novel feature descriptor called local tri directional median differential excitation cooccurrence pattern (LTriDMDECoP) for content based image retrieval is proposed in this paper. The LTriDMDECoP exploits the relationship between the focused or center pixel with its neighboring pixels using differential excitation instead of merely taking advantage of the gray level intensity difference which is sensitive to noise. Further, LTriDMDECoP considers a unique sampling strategy for computation of differential excitation. The proposed method considers median intensity of pixels in three directions to establish the relation between focused pixels with its neighbours using differential excitation. Further, co-occurrences of differential excitation values in local pattern map have been observed in different directions to accomplish fortified feature extraction. The performance of proposed feature descriptor has been tested for image retrieval on Corel-1000 and Corel-5000 bench mark databas...
Power spectral analysis of a signal is nothing bu t analyzing the signal power as a function of f... more Power spectral analysis of a signal is nothing bu t analyzing the signal power as a function of frequency components in the signal. Periodogram, th e fundamental power spectral estimation technique h as the limitation that it is not a consistent estimate , but good at frequency resolution. Hence a number of modifications have been suggested in literature lik Bartlett and Welch etc., to improve the statistic al properties, especially to increase the consistency by reducing the variance of the estimate at the exp ense of frequency resolution. One important task in spectra l estimation is to estimate frequencies in noisy ba ckground with high resolution. This requirement can be achie ved in two steps. One is to develop a good spectral estimate in the sense it should be a consistent estimate and also provide high resolution. Second part is to enhance the sign al detection and/or estimation by reducing the back ground noise. Hence, in this Paper, a new modification for estim a on of Peri...
Distributed Video Coding (DVC) is a video coding method for emerging wireless video surveillance ... more Distributed Video Coding (DVC) is a video coding method for emerging wireless video surveillance networks, wireless video sensor networks and wireless mobile video applications, which is not yet been standardized. DVC is relatively new video coding paradigm, which is not to compete but to complement the popular predictive coding standards such as H.26x, MPEG, VC1 and DivX etc., for the emerging applications. Certain wireless video applications would need low complex encoder, even at the expense of relatively more complex decoder; which is in contrast to the predictive coding standards. Various DVC Architectures developed so far addressed only luma component coding and its Rate Distortion (RD) performance evaluation. In this paper color components (Chroma) coding method of DVC are proposed and results are presented.
An efficient Content-based medical image retrieval (CBMIR) system is imperative to browse the ent... more An efficient Content-based medical image retrieval (CBMIR) system is imperative to browse the entire database to locate required medical image. This paper proposes an effective scheme includes the detection of the boundary of the image followed by exploring the content of the interior boundary region with the help of multiple features. The proposed technique integrates the Texture, Shape features and the relevance feedback mechanism. Differentiate of Gabor Filter used for Texture feature extraction and Moments extract the Region based shape features. The Euclidean distance is used for similarity measure and then these distances are sorted out and ranked. The Recall rate of the medical retrieval system has been enhanced by adapting Relevance Feedback mechanism. The efficiency of the proposed method has been evaluated by using a huge data base by employing multiple features and integrating with Relevance feedback approach. Correspondingly, the Recall Rate has been enormously enhanced ...
Moments of images provide efficient local descriptors and have been used extensively in image ana... more Moments of images provide efficient local descriptors and have been used extensively in image analysis applications. Moments are able to provide invariant measures of shape. On this basis we propose an a new efficient retrieval system using region-based image retrieval system, finding region in the pictures using a new image segmentation method by improved mountain clustering (IMC) technique and features are extracted using a set of orthogonal set of moment functions for describing images The performance of the proposed moments is analyzed in terms of Recall Rate and Retrieval Accuracy. Experimental results demonstrate the superiority of clustering integration with pseudo pseudo-Zernike moments compared with individual features. Index Terms Medical Image Retrieval, Improved Mountain Clustering, Pseudo-Zernike Moments.
Boundary is very commonly defined as line that distinguishes two different regions. Boundary prov... more Boundary is very commonly defined as line that distinguishes two different regions. Boundary provides clarity to human eye in understanding any view. It plays a major role in Medical field, as finding the correct boundary in noisy images is still a difficult task. This paper introduces the new technique of detection using the information of intensity and texture of an image. Our proposed technique detects the boundaries of objects in noisy images using the information from the intensity gradient via the vector image model and the texture gradient via the edge map. we discuss the proposed technique on various medical images using Self organizing map (SOM) clustering provides correct boundaries even in an ill-defined images and multi grey level images. This method is robust and applicable on various kinds of noisy images without prior knowledge of noise properties. Key Word: Boundary Extraction, Edge Following, SOM Clustering.
Medical imaging is a precious and essential tool in healthcare systems, helps the physicians to e... more Medical imaging is a precious and essential tool in healthcare systems, helps the physicians to emanate good quality of treatment. The advancement in medical Technology has resulted in a huge number of medical images which are stored in a database for future purpose. It is very imperative to build an effective retrieval system which browse through entire database in diagnosing the various diseases, helping the therapeutic process and in supporting the medical decision makingprocess. Content based Image Retrieval (CBIR) assists in retrieving the required medical images from a huge database on the basis of their visual features like shape, color and texture. Medical images are generally represented in gray level rather than color. Feature extraction plays an important role in an ever-increasing the performance of the medical image retrieval system. This paper presents a various multiple feature extraction techniques for effective content based medical image retrieval system.
International Journal of Image and Graphics, 2021
Digital image and medical image retrieval from several repositories are improving gradually, so t... more Digital image and medical image retrieval from several repositories are improving gradually, so the capacity of repositories increases rapidly. The semantic space is the main issue on content-based image retrieval (CBIR), which exists among the semantic level as well as increases the data recognized through human and low level visible data obtained through the image. The CBIR system utilizes the deep convolutional neural network (DCNN), which is trained to medical image characterization and the digital image by salp swarm optimization algorithm (SSA). The average classification accuracy for medical image is 86.805%, a mean average precision is 79%, Average Recall Rate (ARR) is 91.7% and [Formula: see text]-measure is 84.9%, are achieved during retrieval task. For image retrieval, the Average Precision Rate (APR) improved from 39%, 40%, 36% and 42.5% to 86.8% and the ARR enhanced from 39.5%, 40.5%, 35.5% and 42.5% to 86.8%. The [Formula: see text]-measure is improved from 39.5%, 40.5...
Indian Journal of Science and Technology, 2012
Research article "Mobile communication" Bhikshapathy et al. Indian Society for Education and Env... more Research article "Mobile communication" Bhikshapathy et al. Indian Society for Education and Environment (iSee) http://www.indjst.org Indian J.Sci.Technol.
Procedia Computer Science, 2016
The content based image retrieval method greatly assists in retrieving medical images close to th... more The content based image retrieval method greatly assists in retrieving medical images close to the query image from a large database basing on their visual features. This paper presents an effective approach in which the region of the object is extracted with the help of multiple features ignoring the background of the object by employing edge following segmentation method followed by extracting texture and shape characteristics of the images. The former is extracted with the help of Steerable filter at different orientations and radial Chebyshev moments are used for extracting the later. Initially the images similar to the query image are extracted from a large group of medical images. Then the search is by accelerating the retrieval process with the help of Support Vector Machine (SVM) classifier. The performance of the retrieval system is enhanced by adapting the subjective feedback method. The experimental results show that the proposed region based multiple features and integrated with classifier and subjective feedback method yields better results than classical retrieval systems.
2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015
The ever-increasing popularity of the use of largervolume image database in various applications,... more The ever-increasing popularity of the use of largervolume image database in various applications, it is an imperative to build an efficient retrieval system to browse through the entire database. Our approach relies on image feature that exploit texture features using second order statistical values such as gray-level co-occurrence matrix (GLCM) , this feature extraction process is as follows: the image is divided into equal sized blocks and the average intensity is computed on the pixels in each block. These values are stored for image matching and similarity measure are based on Euclidean distance, City block of absolute value metric and Murkowski distance. Through the image retrieval experiment, We tested different images database images and measured Recall rate and Error rate as a performance measure which indicate that the use of proposed Texture features is an efficient retrieval technique which has obvious advantage and gives higher recall rate as compared to the histogram technique.
2015 IEEE International Advance Computing Conference (IACC), 2015
An effective content-based image retrieval system is essential to locate required medical images ... more An effective content-based image retrieval system is essential to locate required medical images in huge databases. This paper proposes an effective approach to improve the effectiveness of retrieval system. The proposed scheme involves first, by detecting the boundary of the image, based on intensity gradient vector image model followed by exploring the content of the interior boundary with the help of multiple features using Gabor feature, Local line binary pattern and moment based features. The Euclidean distance are used for similarity measure and then these distances are sorted out and ranked. As a result, the Recall rate enormously improved and Error rate has been decreased when compared to the existing retrieval systems.
BACKGROUND & OBJECTIVE: BCR-ABL oncogene mutations are responsible for the failure of Imatinib (b... more BACKGROUND & OBJECTIVE: BCR-ABL oncogene mutations are responsible for the failure of Imatinib (bcr/abl tyrosine kinase inhibitor (TKI)) treatment in patients with chronic myeloid leukemia (CML). The 2nd generation TKI to be given after Imatinib resistance depends on the type of mutation present. Therefore it is important to routinely test mutation in CML patients who have relapsed or have a sub-optimal response to Imatinib. Sequencing has been widely used to detect bcr/abl Tyrosine kinase domain (TKD) mutations in CML patient as a gold standard but it is expensive , time consuming and not available in most clinical diagnostic labs. This study was planned to screen TKD mutations by High Resolution Melt Curve Analysis (HRM) on real time PCR as a rapid screening tool to detect mutations to be followed by sequencing to confirm the findings of HRM. METHODS: In the present study, 50 patients who have shown no/partial molecular response to Imatinib or have had molecular relapse after one ...
Signal & Image Processing : An International Journal, 2011
Distributed Video Coding (DVC) is a new coding paradigm for video compression, based on Slepian-W... more Distributed Video Coding (DVC) is a new coding paradigm for video compression, based on Slepian-Wolf (lossless coding) and Wyner-Ziv (lossy coding) information theoretic results. DVC is useful for emerging applications such as wireless video cameras, wireless low-power surveillance networks and disposable video cameras for medical applications etc. The primary objective of DVC is low-complexity video encoding, where bulk of computation is shifted to the decoder, as opposed to low-complexity decoder in conventional video compression standards such as H.264 and MPEG etc. There are couple of early architectures and implementations of DVC from Stanford University [2][3] in 2002, Berkeley University PRISM (Power-efficient, Robust, hIgh-compression, Syndrome-based Multimedia coding) [4][5] in 2002 and European project DISCOVER (DIStributed COding for Video SERvices) [6] in 2007. Primarily there are two types of DVC techniques namely pixel domain and transform domain based. Transform domain design will have better rate-distortion (RD) performance as it exploits spatial correlation between neighbouring samples and compacts the block energy into as few transform coefficients as possible (aka energy compaction). In this paper, architecture, implementation details and "C" model results of our transform domain DVC are presented.
IJCSNS, 2007
This paper describes the construction of a tree for a given database of strings for formal langua... more This paper describes the construction of a tree for a given database of strings for formal language query processing. A query can be presented in the form of a Regular Expression (RE) or a Context-Free Grammar (CFG). A special structure for representing the query which can be used for efficient searching is also described. This special structure is a parse tree in the case of a regular expression and Greibach normal form in the case of a context-free grammar. The proposed algorithms are a preprocessing step for search algorithms which bypass the construction of a separate automaton for a given query.
2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO), 2015
In the medical field accurate diagnosis is very crucial for successful treatment. With the rapid ... more In the medical field accurate diagnosis is very crucial for successful treatment. With the rapid development of technology, the ever increasing quantity of medical images is produced in hospitals for diagnosing. Content-Based Image Retrieval (CBMIR) is a technique retrieves similar medical images from large database using visual features such as color, texture and shape. This paper focuses a novel method to increase the performance of Content Based Medical Image Retrieval System (CBMIRS). A multiple features vector gives better-quality performance as compared to a single feature. This paper presents a new approach which takes the advantages of each individual feature. The content of the image extracted with the help of texture and region based shape descriptor, which have better features representation capabilities and are more robust to noise. The texture features are extracted with the help of Gabor filter and chebichef Moments used for Shape features extraction. The similar medical images will be retrieved by comparing the feature vector of the query image with the corresponding feature vectors of the data base images using Euclidian distance as a similarity measure. Experimental results show that proposed method achieves highest retrieval performance in comparison with individual feature based retrieval system.
— the effect of pre-processing of face image in improving the face recognition rate is presented ... more — the effect of pre-processing of face image in improving the face recognition rate is presented in this paper. Three pre-processing steps are used in considering the facial images with dark or bad lighting, low contrast. The pre-processing steps used here are contrast stretching, Homomorphic filtering and conversion of PGM image to
the effect of pre-processing of face image in improving the face recognition rate is presented in... more the effect of pre-processing of face image in improving the face recognition rate is presented in this paper. Three pre-processing steps are used in considering the facial images with dark or bad lighting, low contrast. The preprocessing steps used here are contrast stretching, Homomorphic filtering and conversion of PGM image to Tagged Image File Format (TIFF), Graphics Interchange Format (GIF) and Portable Network Graphics (PNG). In order to reduce the dimension and extracting features Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Kernel Fisher Analysis (KFA) and Kernel Principle Component Analysis (KPCA) are used to see the effect of pre-processing techniques and image formats on these techniques. Results show that the pre-processing steps like contrast stretching and Homomorphic filtering and the database in TIFF, GIF and PNG formats produced excellent improvement and increased the rate of face recognition when compared with AT&T ORL data bases. Keyword...
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Papers by Dr.P.G.Krishna Mohan