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Mechanical Part Surface Defect Detection using Crack Extraction Approach

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 100 - Number 18
Year of Publication: 2014
Priyanka Khandelwal
Pankaj Kumar Gautam

Priyanka Khandelwal and Pankaj Kumar Gautam. Article: Mechanical Part Surface Defect Detection using Crack Extraction Approach. International Journal of Computer Applications 100(18):13-17, August 2014. Full text available. BibTeX

	author = {Priyanka Khandelwal and Pankaj Kumar Gautam},
	title = {Article: Mechanical Part Surface Defect Detection using Crack Extraction Approach},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {100},
	number = {18},
	pages = {13-17},
	month = {August},
	note = {Full text available}


Visual inspection constitutes an important part of quality control in manufacturing industry. The detection of defects on mechanical part surfaces is an important quality control step in the manufacturing of machine products. In this paper, we have introduced a new approach to detect surface defects with varied size, shape in mechanical parts through the use of image processing techniques. First, we apply image edge detection techniques for extracting the edges in an image by identifying pixels where intensity variation is high. Then, for extracting actual defects we reduce gray scale edge information to binary defect information using thresholding. A threshold process will generate a certain amount of noise. So, this noise will removed by a noise filtering technique using the connected component's eccentricity property. Then, based on the highlighted edges, the defect itself should become identifiable by filling the gap between two corresponding edges by comparing gray scale values. The Experimental results show that the proposed method is suitable for extracting the various defects of varying shapes and size in images.


  • G. M. Atiqur Rahaman and Md. Mobarak Hossain, "Automatic Defect Detection and Classification technique from image: A Special Case using Ceramic Tiles", International Journal of Computer Science and Information Security, Vol. 1(1), May 2009.
  • L. Tomczak , V. Mosorov, D. Sankowski, J. Nowakowski," Image Defect Detection Methods for Visual Inspection Systems", in IEEE International Conference on CAD Systems in Microelectronic, pp. 454-456, 2007.
  • Ajay Kumar and Grantham Pang, "Defect Detection in textural materials using Gabor filters" ,IEEE Transactions on Industry Applications,2002, Vol. 38(2):425-440,2002.
  • K. L. Mak, P. Peng, H. YK. Lau, "A real time computer vision systems for detecting defects in textile fabrics", IEEE International Conference on Industrial Technology, pp. 469 – 474, 2005.
  • A. Serdaroglu, A. Ertuzun and A. Ercil, "Defect detection in textile fabric images using wavelet transforms and independent component analysis", Pattern Recognition and Image Analysis, 2006, Vol. 16(1):61-64.
  • Hamid Alimohamdi and Alireza Ahmady, "Detecting skin defect of fruits using optimal Gabor wavelet filter", International conference on Digital image Processing by IEEE, pp. 402-406, 2009.
  • K. N. Sivabalan, Dr. D. Ghanadurai," Detection of defects in digital texture images using segmentation", International Journal of Engineering Science and Technology, 2010, vol. 2 (10): 5187-5191.
  • R. S. Deshmukh, Dr P R Deshmukh," Comparison Analysis For Efficient Defect Detection Algorithm For Gray Level Digital Images Using Median Filters Gabor Filter and ICA", International Journal of Advanced Research in Computer Science and Software Engineering ,2012,vol. 2(1).
  • K. N. Sivabalan and DR. D. Gnanadurai, "Efficient Defect Detection Algorithm for gray level digital images using Gabor Wavelet Filter and Gaussian Filter", International Journal of Engineering Science and Technology, Vol. 3, No. 4,2011.
  • Gui-mei Zhang, Shao-ping Chen, Jia-ni Liao, "Otsu Image Segmentation Algorithm Based on Morphology and Wavelet Transformation", in IEEE International Conference on Computer Research and Development , vol. 1, pp. 279-283, 2011.
  • Fari Muhammad Abubakar,"Study Of Image Segmentation By Using Edge Detection Techniques", International Journal of Engineering Research & Technology, Vol. 1 Issue 9, November- 2012.
  • Poonam deep Kaur and Raman Maini," Performance Evaluation of Various Thresholding Methods using Canny Edge Detector, International Journal of Computer Applications(IJCA),Vol. 71 No. 9,2013.
  • Febriliyan Samopa and Akira Asano," Hybrid Image Thresholding Method using Edge Detection", IJCSNS International Journal of Computer Science and Network Security, VOL. 9 No. 4, 2009.
  • H. Y. T. Ngan, G. K. H. Pang, N. H. C. Yung, "Automated fabric defect detection—a review", Image Vision Computing, Vol. 29 (7):442–458, 2011.