Yogita K. Dubey

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A new algorithm for the segmentation of brain MR images, using intuitionistic fuzzy clustering (IFCM), is proposed in this paper. The algorithm uses intuitionistic fuzzy representation of image to deal with variations in pixel intensities of brain MR images. The proposed intuitionistic fuzzy clustering algorithms segments brain MR image into three regions,(More)
The fuzzy c-means (FCM) algorithm is a very popular algorithm in the field of image segmentation because of its simplicity and less sensitivity to noise and it is widely used in the field of engineering disciplines. The FCM membership function can handle the overlapped clusters efficiently with predefined number of clusters, but this algorithm are unable to(More)
Cardiovascular diseases are a major health concern worldwide. The left ventricle and in particular the endocardium is a structure of particular interest since it performs the task of pumping oxygenated blood to the entire body. Therefore, segmentation of the left ventricle in echocardiography images is a task with important diagnostic power. More(More)
A testing module in the life cycle of a software development plays a crucial role for its development and its successful deployment using the defined cases. For this previous practitioner incorporated data mining techniques to reduce the number of test cases. During the software development process appropriate selection of unit tests is vital when many unit(More)
Software testing is one of the most important parts of the software development. It also takes too much time to complete, because there are test cases are used for the testing of the software. So data mining techniques are used to improve the performance of the testing by reducing the size of the test cases. In this paper a Parallel Early Binding Recursive(More)
— In accordance with the characteristics of urban high-resolution color remote sensing images, we put forward an object shadow detection method. In this method, during image segmentation, shadow features are taken into consideration and after that using statistical feature of the images, suspected shadows are extracted. According to object properties and(More)
In this paper, a method for image segmentation using multiscale intuitionistic fuzzy roughness measure is proposed. The traditional roughness measure tends to over-focus on the little important homogeneous regions but is not accurate enough to measure the homogeneity in an image. By applying the theories of scale-space and using intuitionistic fuzzy(More)
In this paper, a method for color image segmentation using multiscale intuitionistic fuzzy roughness measure is proposed. The traditional roughness measure tends to over focus on the little important homogeneous regions but is not accurate enough to measure the homogeneity in an image. By applying the theories of scale space and using intuitionistic fuzzy(More)