Image Segmentation using Extended Edge Operatorfor Mammographic Images

K Naresh Kumar; G L N V Kartheek; G V S Ch S L V Prasad

doi:10.46243/jst.2021.v6.i06.pp174-179

Authors

K Naresh Kumar
G L N V Kartheek
G V S Ch S L V Prasad

DOI:

https://doi.org/10.46243/jst.2021.v6.i06.pp174-179

Keywords:

mammographic images, segmentation, edge operator

Abstract

Detection of edges in an image is a very important step towards understanding image features. Since edges oftenoccur at image locations representing object boundaries, edge detection is extensively used in image segmentation when images are divided into areas corresponding to different objects. This can be used specifically for enhancing the tumor area in mammographic images. In this paper extended Sobel , Prewitt and Kirsch edge operators are proposed for image segmentation of mammographic images. Edges and tumor location can be seen clearly by using this method. For comparison purpose Gray level co-occurrence matrix, watershed algorithm, present Sobel, Prewitt and Kirsch edge operators are used and their results are displayed.

References

Huertas, A. and Medioni, G., ―Detection of intensity changes with sub pixel accuracy using Laplacian-Gaussian masks,‖ IEEE Trans. On Pattern Analysis and Machine Intelligence, PAMI, vol. 8, pp. 651–664, 1986

Leila Shafarenko and Maria Petrou, ― Automatic Watershed Segmentation of Randomly Textured Color Images‖, IEEE Transactions on Image Processing, Vol.6, No.11, pp.1530-1544, 1997

Basim Alhadidi, Mohammad H. et al, ― Mammogram Breast Cancer Edge Detection Using Image Processing Function‖ Information Technology Journal 6(2):217- 221,2007,ISSN-1812-5638 Published by: Longman Publishers www.jst.org.in Page | 179 View publication stats