Medical Image Retrieval – Performance Comparison using Texture Features

Hebbar, Harishchandra H and Mushigeri, Sumanth and Niranjan, U C (2014) Medical Image Retrieval – Performance Comparison using Texture Features. International Journal of Engineering Research and Development, 9 (9). pp. 30-34. ISSN 2278-067X

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Image retrieval is a specialized search to find images of interest. User may give a keyword, sketch or image itself to image search engine to retrieve back relatively similar images from the already stored image database. The similarity used as the search criteria could be based on features such as text, tag, color distribution of images (histogram), texture, shape, etc. The limitation of the text based retrieval is subjected to human interpretation of the mages in the form of combination of few texts/ key words. This is a very cumbersome process and could be highly error prone also. However, when it comes to medical images low level features of the image are more important than the semantics of the images. The low level features generally include color, texture and shape. The extraction of these features needs to be done for every image and to be pre-stored in the database to retrieve the images quickly. The retrieval method based on the content is known as Content Based Image Retrieval (CBIR).

Item Type: Article
Uncontrolled Keywords: CBIR, GLCM, Contrast, Dissimilarity, Homogeneity, Angular Second Moment, Entropy, Precision, Recall, Retrieval time
Subjects: Information Sciences > MCIS Manipal
Depositing User: MIT Library
Date Deposited: 08 Apr 2017 09:12
Last Modified: 08 Apr 2017 09:12

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