Title: An approach to extract edge maps in infrared based breast images using inverse Perona-Malik diffusion filter

Authors: J. Thamil Selvi; Ganesan Kavitha; C. Manoharan Sujatha

Addresses: Department of Electronics and Communication Engineering, Sri Sairam Engineering College, Chennai, India; Department of Electronics and Communication Engineering, Anna University, Chennai, India ' Department of Electronics Engineering, Madras Institute of Technology Campus, Anna University, Chennai, India ' Department of Electronics and Communication Engineering, Anna University, Chennai, India

Abstract: Infrared thermography is the adjunctive tool for early diagnosis of breast cancer. The infrared breast images are of low Signal to Noise Ratio (SNR) and amorphous in nature which makes analysis a challenging task. In this work, an attempt is made to extract the edge map from infrared breast images using inverse Perona-Malik (PM) model. This non-linear filter varies the diffusion near the interferences and edges using inverse gradient and new nearest-neighbour scheme. The edge maps are extracted for various gradient thresholds. The statistical features such as average gradient, contrast, entropy and variance are extracted from the edge map to find the optimal gradient threshold. The diffused image of optimal gradient threshold value is validated using SNR. Results show that the statistical features are found to have maximum value for the gradient threshold of 5. It is also observed that SNR obtained from the diffused image is improved by 30 dB compared to raw image. Inverse PM model is found to reduce the noise and enhance the edges. The integration of denoising and edge map extraction would result in accurate segmentation and aid for early diagnosis.

Keywords: breast thermal images; inverse PM model; average gradient; contrast; entropy; variance; SNR.

DOI: 10.1504/IJBET.2018.095206

International Journal of Biomedical Engineering and Technology, 2018 Vol.28 No.3, pp.261 - 272

Received: 12 May 2016
Accepted: 26 Aug 2016
Published online: 02 Oct 2018 *

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