Modelling Human Segmentation Trough Color and Space Analysis

Borràs, Josep M.; Lladós, Josep

doi:10.1007/978-3-642-03767-2_109

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2018

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Cited by 1 publication

(2 citation statements)

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“…Ref. [16] proposeed an algorithm that models the human-based perception according to Gestalt laws of similarity and proximity. The mean shift clustering is employed to translate laws into analysis of color layout of an image.…”

Section: Model-based Methodsmentioning

confidence: 99%

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Segmentation of images by color features: A survey

et al. 2018

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Image segmentation is an important stage for object recognition. Many methods have been proposed in the last few years for grayscale and color images. In this paper, we present a deep review of the state of the art on color image segmentation methods; through this paper, we explain the techniques based on edge detection, thresholding, histogram-thresholding, region, feature clustering and neural networks. Because color spaces play a key role in the methods reviewed, we also explain in detail the most commonly color spaces to represent and process colors. In addition, we present some important applications that use the methods of image segmentation reviewed. Finally, a set of metrics frequently used to evaluate quantitatively the segmented images is shown.

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Section: Model-based Methodsmentioning

confidence: 99%

“…The GCE computes how a segmented image is viewed as the refinement of other. A measure of error at each pixel x i can be written as [16,119] :…”

Section: Global Consistency Errormentioning

confidence: 99%