Segmentation of Diabetic Foot Ulcer using Gaussian Mixture Model and Fuzzy KNN Algorithm
C. Karthikeyini1, P. Umadevi2
1C. Karthikeyini, Senior Professor, Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore (Tamil Nadu), India.
2P. Umadevi, PG Scholar, Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 22 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1602-1606 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B11130882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1113.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In recent years image processing gained the attention of many researches on diabetic foot ulcer (DFU) which is caused by strange increase of blood glucose results nerve injury and leads to amputation. This paper discusses about denoising element on wound by GMM method and image segmentation performed using fuzzy K-NN method. The image is denoised by Gaussian mixture model. The fuzzy KNN algorithm is used for segmentation of wound area from the background image. Further, for analysis the segmented area is subjected to homomorphic filtering and gabor filtering. The performance parameters values such as PSNR, MSE and AMBE are calculated from the resultant image. These values are compared with the Gaussian filtered image values.
Keywords: Gaussian Mixture Model, Parameter Measurement, Segmentation on Fuzzy K-NN.
Scope of the Article: Algorithm Engineering