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Corner Detection Algorithm Based on Cellular Neural Networks (CNN) and Differential Evolution (DE)

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Recent Metaheuristic Computation Schemes in Engineering

Part of the book series: Studies in Computational Intelligence ((SCI,volume 948))

Abstract

Corner detection represents one of the most important steps to identify features in images. Due to their powerful local processing capabilities, Cellular Nonlinear/Neural Networks (CNN) are commonly utilized in image processing applications such as image edge detection, image encoding and image hole filling. CNN perform well for locating corner features in binary images. However, their use in grayscale images has not been considered due to their design difficulties. In this chapter, a corner detector based on CNN for grayscale images is presented. In the approach, the original processing scheme of the CNN is modified to include a nonlinear operation for increasing the contrast of the local information in the image. With this adaptation, the final CNN parameters that allow the appropriate detection of corner points are estimated through the Differential evolution algorithm by using standard training images. Different test images have been used to evaluate the performance of the presented corner detector. Its results are also compared with popular corner methods from the literature. Computational simulations demonstrate that the presented CNN approach presents competitive results in comparison with other algorithms in terms of accuracy and robustness.

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Authors and Affiliations

  1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas & Alma Rodríguez

  2. Facultad de Ingeniería, Universidad Panamericana, Zapopan, Jalisco, Mexico

    Alma Rodríguez, Avelina Alejo-Reyes & Carolina Del-Valle-Soto

  3. Centro de Eneñanza Técnica Industrial, Universidad de Guadalajara, Guadalajara, Mexico

    Alma Rodríguez

Authors
  1. Erik Cuevas
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  2. Alma Rodríguez
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  3. Avelina Alejo-Reyes
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  4. Carolina Del-Valle-Soto
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Correspondence to Erik Cuevas .

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Cuevas, E., Rodríguez, A., Alejo-Reyes, A., Del-Valle-Soto, C. (2021). Corner Detection Algorithm Based on Cellular Neural Networks (CNN) and Differential Evolution (DE). In: Recent Metaheuristic Computation Schemes in Engineering. Studies in Computational Intelligence, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-66007-9_4

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