Firing Pin Impression Segmentation using Canny Edge Detection Operator and Hough Transform

Authors

  • Norazlina Abd Razak Faculty of Electronics & Computer Engineering, Universiti Teknikal Malaysia Melaka, Malaysia. School of Mathematical Sciences, Faculty of Sciences and Technology, Universiti Kebangsaan Malaysia, Malaysia
  • Choong-Yeun Liong School of Mathematical Sciences, Faculty of Sciences and Technology, Universiti Kebangsaan Malaysia, Malaysia
  • Abdul Aziz Jemain School of Mathematical Sciences, Faculty of Sciences and Technology, Universiti Kebangsaan Malaysia, Malaysia
  • Nor Azura Md Ghani Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Malaysia
  • Shahrudin Zakaria Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka, Malaysia
  • Hanissah Mohamad@Sulaiman Faculty of Electronics & Computer Engineering, Universiti Teknikal Malaysia Melaka, Malaysia.

Keywords:

Canny Edge Detection, Hough Transform, Firing Pin Impression, Segmentation,

Abstract

Firearms identification based on the forensic ballistics specimen is crucial in solving criminal case in a short time. Currently, the firearms examiners perform authentication by visual observation. Due to observation of large evidence database, the experts normally take a long time to identify the firearms. As a result, computerized firearms identification should be implemented in order to perform the identification faster. The computerized identification involves image preprocessing, segmentation, feature extraction and classification. Therefore, in order to reduce computational time, the segmentation has to be performed automatically. The main objective of this study is to perform the segmentation of firing pin impression by using Canny edge detection operator improvised with Hough transform. The performance of segmentation in detecting the central image of firing pin impression has achieved 93% segmentation accuracy

References

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Published

2017-01-01

How to Cite

Abd Razak, N., Liong, C.-Y., Jemain, A. A., Md Ghani, N. A., Zakaria, S., & Mohamad@Sulaiman, H. (2017). Firing Pin Impression Segmentation using Canny Edge Detection Operator and Hough Transform. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(1), 23–26. Retrieved from https://jtec.utem.edu.my/jtec/article/view/910

Issue

Vol. 9 No. 1: January - March 2017

Section

Articles

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