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Analysis and identification of kidney stone using Kth nearest neighbour (KNN) and support vector machine (SVM) classification techniques

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Abstract

Kidney stone detection is one of the sensitive topic now-a-days. There are various problem associates with this topic like low resolution of image, similarity of kidney stone and prediction of stone in the new image of kidney. Ultrasound images have low contrast and are difficult to detect and extract the region of interest. Therefore, the image has to go through the preprocessing which normally contains image enhancement. The aim behind this operation is to find the out the best quality, so that the identification becomes easier. Medical imaging is one of the fundamental imaging, because they are used in more sensitive field which is a medical field and it must be accurate. In this paper, we first proceed for the enhancement of the image with the help of median filter, Gaussian filter and un-sharp masking. After that we use morphological operations like erosion and dilation and then entropy based segmentation is used to find the region of interest and finally we use KNN and SVM classification techniques for the analysis of kidney stone images.

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Authors and Affiliations

  1. Department of ECE, Hindu College of Engineering Industrial Area, Sonepat, Haryana, 131001, India

    Jyoti Verma, Madhwendra Nath, Priyanshu Tripathi & K. K. Saini

Authors
  1. Jyoti Verma
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  2. Madhwendra Nath
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  3. Priyanshu Tripathi
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  4. K. K. Saini
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Corresponding author

Correspondence to Jyoti Verma.

Additional information

The article is published in the original.

Jyoti Verma is B. Tech from MDU Rohtak (Haryana), Pursuing M. Tech from DCRUST (Haryana), India. She is a young Technocrat and researcher. Her area of Interest is Image processing. She has published various research papers in National, International conferences.

Madhwendra Nath is B. Tech., M. Tech. from N.I.T. Jalandhar (Punjab), India. Currently, He is working as an Assistant Professor in Hindu college of Engineering Sonepat, Haryana, India. His area of Interest is Signal Processing and image Biometric Security. He has published various research papers in National, International and IEEE international conferences.

Priyanshu Tripathi is B.Tech., M.Tech. from N.I.T. Jalandhar (Punjab), India. He is a young Technocrat and researcher. Currently, He is working as an Assistant Professor in Hindu college of Engineering Sonepat, Haryana, India. His area of Interest is Robotics and Image processing. He has published various research papers in National, International and IEEE international conferences.

Kamal Kumar Saini is B.E., M.Tech. and PhD in Electronics and Communication Engineering. Currently, He is Director-Principal of Hindu College of Engineering Sonepat, Haryana, India. His Research area and area of interest is Optical Communication, Chaos based comm., Satellite Communication and Reliability Engineering. He has published more than 500 research papers in various reputed international journals, international conferences and IEEE International Transactions. He has guided Dissertation of more than 30 M.Tech. students and 7 Ph.D. scholars.

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Verma, J., Nath, M., Tripathi, P. et al. Analysis and identification of kidney stone using Kth nearest neighbour (KNN) and support vector machine (SVM) classification techniques. Pattern Recognit. Image Anal. 27, 574–580 (2017). https://doi.org/10.1134/S1054661817030294

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