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Literature survey is most important for understanding and gaining much more knowledge about specific area of a subject. In this paper a survey on content based image retrieval presented. Content Based Image Retrieval (CBIR) is a technique which uses visual features of image such as color, shape, texture, etc... to search user required image from large image(More)
Feature Selection (FS) aims to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. Rough set theory (RST) has been used as such a tool with much success. In the supervised FS methods, various feature subsets are evaluated using an evaluation function or metric to select(More)
Feature Selection (FS) aims to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. Rough set theory (RST) has been used as such a tool with much success. In the supervised FS methods, various feature subsets are evaluated using an evaluation function or metric to select(More)
— Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the(More)
— Feature means countenance, remote sensing scene objects with similar characteristics, associated to interesting scene elements in the image formation process. They are classified into three types in image processing, that is low, middle and high. Low level features are color, texture and middle level feature is shape and high level feature is semantic gap(More)
Mass classification of objects is an important area of research and application in a variety of fields. In this paper, we present an efficient computer-aided mass classification method in digitized mammograms using Fuzzy K-Nearest Neighbour Equality (FK-NNE), which performs benign or malignant classification on region of interest that contains mass. One of(More)
— Image segmentation is a crucial step in a wide range of method image processing systems. It is useful in visualization of the different objects present in the image. In spite of the several methods available in the literature, image segmentation still a challenging problem in most of image processing applications. The challenge comes from the fuzziness of(More)
Mammograms are the soft X-rays kind of imaging technique used for the detection of any lesions or cysts in breasts. Digital mammograms have many kinds of artifacts that affect the accuracy of the detection of tumor tissues in the automated Computer Aided Detection (CAD) system for mammograms. Preprocessing helps to remove such artifacts is an important(More)
— The removal of speckle noise in ultrasound medical image is still a challenging one in medical image processing and analysis. Since, there is no common filter for speckle reduction. In this paper, we proposed six nonlinear techniques with combiner approach for image filtering especially for speckle removal task, viz., MNHP Filter, ANHP Filter, TNHP(More)
Breast Cancer involves the uncontrolled growth of abnormal cells that have mutated from normal tissues. A radiologist looks for certain signs and characteristics indicative of cancer when evaluating a mammogram. The main task is to obtain the locations of suspicious regions to assist radiologists in diagnosis. Image segmentation has been approached from a(More)