A Modified Harris Corner Detection for Breast IR Image

Chia-Yen Lee, Hao-Jen Wang, Chung-Ming Chen, Ching-Cheng Chuang, Yeun-Chung Chang and Nien-Shiang Chou

Mathematical Problems in Engineering, 2014, vol. 2014, 1-12

Abstract:

Harris corner detectors, which depend on strong invariance and a local autocorrelation function, display poor detection performance for infrared (IR) images with low contrast and nonobvious edges. In addition, feature points detected by Harris corner detectors are clustered due to the numerous nonlocal maxima. This paper proposes a modified Harris corner detector that includes two unique steps for processing IR images in order to overcome the aforementioned problems. Image contrast enhancement based on a generalized form of histogram equalization (HE) combined with adjusting the intensity resolution causes false contours on IR images to acquire obvious edges. Adaptive nonmaximal suppression based on eliminating neighboring pixels avoids the clustered features. Preliminary results show that the proposed method can solve the clustering problem and successfully identify the representative feature points of IR breast images.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2014/902659.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2014/902659.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:902659

DOI: 10.1155/2014/902659

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().