Firing pin impression segmentation using Canny edge detection operator and Hough transform

Norazlina Abd Razak, Choong Yeun Liong, Abdul Aziz Jemain, Nor Azura Md Ghani, Shahrudin Zakaria, Hanissah MohamadSulaiman

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)23-26
Number of pages4
JournalJournal of Telecommunication, Electronic and Computer Engineering
Volume9
Issue number1
Publication statusPublished - 1 Jan 2017

Fingerprint

Hough transforms
Edge detection
Ballistics
Image segmentation
Authentication
Mathematical operators
Feature extraction

Keywords

  • Canny edge detection
  • Firing pin impression
  • Hough transform
  • Segmentation

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

Firing pin impression segmentation using Canny edge detection operator and Hough transform. / Razak, Norazlina Abd; Liong, Choong Yeun; Jemain, Abdul Aziz; Md Ghani, Nor Azura; Zakaria, Shahrudin; MohamadSulaiman, Hanissah.

In: Journal of Telecommunication, Electronic and Computer Engineering, Vol. 9, No. 1, 01.01.2017, p. 23-26.

Research output: Contribution to journalArticle

Razak, Norazlina Abd ; Liong, Choong Yeun ; Jemain, Abdul Aziz ; Md Ghani, Nor Azura ; Zakaria, Shahrudin ; MohamadSulaiman, Hanissah. / Firing pin impression segmentation using Canny edge detection operator and Hough transform. In: Journal of Telecommunication, Electronic and Computer Engineering. 2017 ; Vol. 9, No. 1. pp. 23-26.
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