Research Article Open Access

Local Features Supported by the Complement Feature for Image Segmentation

Salah Ameer1
  • 1 Ontario Colleges, Canada
American Journal of Engineering and Applied Sciences
Volume 13 No. 3, 2020, 327-332

DOI: https://doi.org/10.3844/ajeassp.2020.327.332

Submitted On: 3 June 2020
Published On: 7 July 2020

How to Cite: 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

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.

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Keywords

  • Image Thresholding
  • Image Segmentation
  • Eigen Value