Edge detection of femur bone - A comparative study

Harish Kumar, Ashvini Chaturvedi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Edge detection of femur in X - ray images is an important pre processing step in segmentation and 3 - D reconstruction of femur. A typical femur image is generally very noisy. A lot of edges caused by the muscles and other bones can easily mislead the edge detection algorithm. Particularly, the femoral head overlapping the pelvic bone makes it very difficult to get a clear edge of the femur head. The edge caused by the abdominal muscles around the femur shaft can also mislead the edge detection algorithm. These extraneous edges and noise make edge detection very difficult and challenging, which is not well solved. Classical edge detectors fail miserably due to the high inhomogeneous nature of the femur X - ray images. This paper compares a new approach to edge detection of femur X - ray images using Wavelet transforms with classical edge detectors. The Wavelet based edge detection algorithm combines the coefficients of wavelet transforms on a series of scales and significantly improves the result. It is found that Wavelet based technique works much better than classical edge detectors.

Original languageEnglish
Title of host publicationProceedings of the 2010 International Conference on Signal and Image Processing, ICSIP 2010
Pages281-285
Number of pages5
DOIs
Publication statusPublished - 01-12-2010
Externally publishedYes
Event3rd IEEE International Conference on Signal and Image Processing, ICSIP 2010 - Chennai, India
Duration: 15-12-201017-12-2010

Conference

Conference3rd IEEE International Conference on Signal and Image Processing, ICSIP 2010
CountryIndia
CityChennai
Period15-12-1017-12-10

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Kumar, H., & Chaturvedi, A. (2010). Edge detection of femur bone - A comparative study. In Proceedings of the 2010 International Conference on Signal and Image Processing, ICSIP 2010 (pp. 281-285). [5697429] https://doi.org/10.1109/ICSIP.2010.5697429