Digital Image Processing

M. Vanitha ¹, M. Muthuraman ²

Affiliations
1 Department of Computer Science, J.J. College of Arts and Science, Pudukkottai, IN
2 Department of Computer Science, H.H. the Rajah’s College, Pudukkottai, IN

Abstract

Content-based image retrieval (CBIR) is one of the most interesting research area in the subject of computer science and image processing. Much progress has been made over for the last ten years. In this paper a comprehensive review on the content-based image retrieval and its application in medical image diagnosis have been addressed. The present review includes current trend in this field and certain gap of knowledge for the feature development. Research in the field of image retrieval, is active and fast advancing since 1990. A remarkable progress in theoretical as well as system development has been achieved. However still there are many challenging areas in this discipline. This article gives a complete overview of available literature in the field of content based access to medical image those have been published for the last 10 years. Furthermore it gives what is achieved to date? It also deals with the state of art CBIR application in medical domain.

Keywords

A Comprehensive Account on CBIR, Present Trend of CBIR, Review of CBIR in Medical Image Processing.

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M. Vanitha ¹, R. Balasubramanian ²

Affiliations
1 Mother Teresa University, Kodaikannel, IN
2 EBET Knowledge Park, Tirupur, IN

Abstract

To determine the accuracy of normal tissue scan images from the abnormal cases, the GLCM (Grey-Level Co-occurrence matrix) and their derived parameters such as homogeneity of the images and energy level calculations were approached. These structural and textural parameters were calculated by using mathematical formulae. In each case 20 abdominal scan images of both normal and abnormal patients were employed. The data generated out of this present investigation was tabulated and statistically analyzed. The analysis for energy level on the images disclosed that there was a clear distinguish between normal tissue and abnormal tissue. The above results are discussed with relation to the accuracy.

Keywords

Textural Features of CT Images, Statistical Design For Image Studies, Medical Image Textural Analysis.

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