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- W2768045646 abstract "In this work two computer vision approaches are presented, these are mainly based on the mathematical morphology theory; first a technique for scale space analysis is proposed, on the other hand a new transformation for image normalization and constrast enhancement is introduced. Various works reported in the literature show that scale space analysis is of great importance in a wide range of computer vision tasks, such as, pattern recognition, coding, segmentation, and so on. This fact yielded to propose a scale space approach based on morphological reconstruction transformation which have very advantageous properties, as, contour preservation, major noise inmunity and offering a way to perform segmentation of the image. The contrast operator uses the background notion and a human visual perception model (Weber Law), allowing the normalization and contrast enhancement in images with poor illumination. In this work the most important properties will be presented and the performance of both approaches will be illustrated with various examples." @default.
- W2768045646 created "2017-11-17" @default.
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- W2768045646 date "2008-05-01" @default.
- W2768045646 modified "2023-09-27" @default.
- W2768045646 title "Análisis multiescala morfológico y compensación en iluminación en imágenes digitales" @default.
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