Morphological Operators

A Computer Aided Diagnosis (CAD) system is proposed for the detection of pleural effusion and
pneumothorax, which affect the pleural membranes of the lungs. The accuracy of a CAD system is largely
dependent on the efficiency and preciseness of its segmentation system. The segmentation technique used
here extracts the lungs and the regions affected by pleural effusion using conventional thresholding techniques
like Otsu’s and iterative thresholding, followed by morphological operations. The chest CT slices are initially
preprocessed to remove the gaussian noise by using a Gaussian filter. Morphological operations are then applied,
to segment the lung parenchyma as well as to extract the region of interest (ROI). Texture features are next
extracted from the ROIs, which are used to compute the feature vectors. These are used to train a neural network
classifier. After the training process is complete, the query images are given to the system for classification.

The use of products and services of the mobile telecommunication industry becomes a part and parcel of each human being around the globe irrespective of the age. It is hardly visible to see people without the use of telecommunication technology in today's world. The present research article examines the alarming signal of market saturation of telecommunication companies in Malaysia as internal competitors is increasing in number and age restriction of 18 years and above for legally registered owners of mobiles. The saturation in the mobile telecommunication market is due to the relative low birth rate in Malaysia, the eligible population to register a mobile phone is not proportional to telecommunication service providers. In addition, there is also new Mobile Virtual Network Operators (MVNO) which magnifies the problem further. Otherwise the local service providers have efficient and effective networking with other countries; the sustainability of the telecommunication company's performance is at stake.

Extraction of coronary artery from coronary angiography is an important goal to improve the diagnosis and treatment of coronary artery disease. This paper presents the extraction of coronary artery blood vessels using Morphological operators. The paper involves two stages. The first stage involves the application of the basic Morphological operator in which the brightness of the arteries was improved using the dilation operator. The second stage presents the background correction using thresholding technique followed by advanced morphological operations whereby the unwanted background particles were removed and the blood vessels of the coronary arteries are extracted. Simulation results show the efficiency of the extraction of coronary artery by the proposed method. The simulation is implemented using Laboratory Virtual Instrumentation Engineering Workbench (Lab VIEW) version 13.

Morphological filters erosion and dilation plays an important role for highlighting the buildings and roads areas in aerial images. These filters give better results for classification of particular building and road areas in Images which are our region of interest. Image processing is a dynamic field and in recent years it is applied in many areas like medical sciences, remote sensing, military defense system, physical sciences and aerospace for useful purposes. This research paper focuses the study of highly resoluted aerial image of populated area. By applying different image processing techniques on aerial images like red band extraction, edge detection, enhanced gray level, texture features, red band replacement, binary threshold and finding the objects and classes of the image. By considering a particular range of buildings and roads objects then reconstruct the subjected images. At the end these buildings and road areas are highlighted by applying morphological filter erosion and dilation. We have taken the aerial image of Lahore Canal bank Road by Google earth and implemented all the above discussed techniques on it. The implemented techniques highlighted the building and road areas with red color.