A New Corner Detection Operator for Multi-Spectral Images

Corner detection is a crucial image processing technique that has a wide range of application, including motion detection, image registration, video tracking, and object recogni-tion. Most proposed approaches for corner detection are based on gray-scale images, despite it has been shown that color infor-mation can greatly improve the quality of corners detection. This paper aims to introduce a new operator that identifies the second-order image information for multi-spectral images. The operator is developed using the multi-spectral gradient and differential structures of the image. Consequently, the eigenvectors of the proposed operator are used for detecting corners. A comparative study is conducted using synthetic and real images, and the result confirms that the proposed approach performs better compared with two other approaches for detecting corners.

@article{Houari2021,
  title     = {A New Corner Detection Operator for Multi-Spectral Images},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {4},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Hassan El Houari and Ahmed Fouad El Ouafdi},
  doi       = {10.14569/IJACSA.2021.0120491},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120491}
}