Abstract
In this chapter, an alternative to the traditional thresholding of images is presented for segmentation. Most threshold-based segmentation procedures use the histogram of the image as the only source of information to partition the image; although this approach perform well on most scenarios, it only relies on the intensity of the pixels while ignoring the spatial relationships. Contextual information can help to enhance the quality of the segmented images as it considers not only the value of the pixel but also its vicinity. The energy curve was designed to bring spatial information into a curve with the same properties as the histogram. Thus, most thresholding approaches can be directly applied to the energy curve. In this chapter, the performance of the segmentation of images using the energy curve is analyzed using the Ant-Lion Optimizer with both Otsu and Kapur methods.
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Oliva, D., Abd Elaziz, M., Hinojosa, S. (2019). Contextual Information in Image Thresholding. In: Metaheuristic Algorithms for Image Segmentation: Theory and Applications. Studies in Computational Intelligence, vol 825. Springer, Cham. https://doi.org/10.1007/978-3-030-12931-6_15
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