Local Features Supported by the Complement Feature for Image Segmentation
Salah Ameer1 Show affiliations
- Ontario Colleges, Canada
American Journal of Engineering and Applied Sciences, Volume 13, Issue 3, pp. 327–332 · doi.org/10.3844/ajeassp.2020.327.332
Abstract
An Eigen formulation is proposed for image thresholding/segmentation. A vector composed of local features, normalized intensity of each pixel and that of the neighboring pixels, is used to represent each pixel. A “complement” component is appended to this vector to produce a “unit” vector. The auto-correlation matrix is computed for each pixel in the image using this unit vector. The first component (corresponding to the intensity of the current pixel) from all Eigen vectors, obtained from the auto-correlation matrix, are used as multi-level thresholds. Similar procedure can be adopted using powers of the current pixel intensity value. In general, more than one threshold can be obtained. Results on a wide range of images are demonstrated to show the effectiveness of the proposed schemes.
Licence and reuse
Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.
How to reuse this articleResponses (0)
About this article
Ameer, S. (2020). Local Features Supported by the Complement Feature for Image Segmentation. American Journal of Engineering and Applied Sciences, 13(3), 327–332. https://doi.org/10.3844/ajeassp.2020.327.332
- Licence
- CC BY 3.0
- Issue
- Volume 13, Issue 3
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
