ENLARGEMENT OF EFFICIENT AUTOMATIC VOLUMETRIC MAMMOGRAPHIC IMAGE CLASSIFICATION BASED ON ROBUST FEATURES.
- Department of ECE, J K KNattraja College of Engineering and Technology, Namakkal- 638183, Tamil Nadu, India
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Image classification is always a supporting and difficult task for medical systems. Mammographic images contain various features like space, distance, circumscribed masses, speculated masses and micro calcification. This paper focuses on classifying mammographic images based on the region of interest. The images may be looking blurred due to the variation in illumination, intensity and contrast which cannot be directly processed. Hence, multilevel filters have been used to enhance the image. The integral images are generated from the input image to normalize the contrast of the image. Various filters and equalization techniques have been used to uniformly distribute the gray values in the image thereby the noise is eliminated to enhance the input image for further processing. The texture features, their shape, and spatial features are extracted to compute the growth of the anatomic features. Therefore, the quality of the image classification which is an ultimate aim of this paper is improved. Therefore, the quality of the image classification which is an ultimate aim of this proposed is improved. The result shows that the proposed method has increased the classification accuracy.
[S.Julian Savari Antony. (2016); ENLARGEMENT OF EFFICIENT AUTOMATIC VOLUMETRIC MAMMOGRAPHIC IMAGE CLASSIFICATION BASED ON ROBUST FEATURES. Int. J. of Adv. Res. 4 (6). 505-512] (ISSN 2320-5407). www.journalijar.com
Article DOI: 10.21474/IJAR01/790 DOI URL: http://dx.doi.org/10.21474/IJAR01/790
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