To Predict the Gender and Fracture from Skull X-ray Image from Various Image Analysis
B.J. Bipin Nair1, Mathews Jose2, S. Harikrishna3
1B.J. Bipin Nair, Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
2Mathews Jose, Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
3S. Harikrishna, Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 01 May 2019 | Manuscript Published on 08 May 2019 | PP: 90-94 | Volume-7 Issue-5S3 February 2019 | Retrieval Number: E11170275S19/19©BEIESP
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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 our proposed work we are going to predict the gender and detect fracture from archeological skull image using various image analysis techniques. Due to the huge technological advancements in forensics as well as healthcare, determining the gender and predicting the fracture is easy with X-rays images. However, the major drawback of existing work is that conclusions are drawn based upon the prediction made by doctors manually. But from our system, using various medical image processing techniques like Histogram Equalization, Prewitt, Sobel and Canny Edge Detection algorithm we can predict the skull bones fracture, and by feature extraction we can predict gender using ROI. Our system works on the various efficient methods and algorithms developed to perform various operations on skull images, but these operations make life easy for the surgeons.
Keywords: Histogram Equalization, Sobel, Prewitt and Canny Edge Detection, Region of Interest (ROI).
Scope of the Article: Image analysis and Processing