2006
DOI: 10.1093/ietisy/e89-d.3.1231
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Grayscale Image Segmentation Using Color Space

Abstract: A novel approach for segmentation of grayscale images, which are color scene originally, is proposed. Many algorithms have been elaborated for a grayscale image segmentation. All those approaches have been discussed in a luminance space, because it has been considered that grayscale images do not have any color information. However, a luminance value has color information as a set of corresponding colors. In this paper, an inverse mapping of luminance values is carried out to CIELAB color space, and the image … Show more

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Cited by 11 publications
(12 citation statements)
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“…In color segmentation of an image, the objective is to spatially separate regions based on similarities inside each region and differences among distinct regions. The way to undertake the segmentation of color varies from the empirical evaluation of various color spaces (Horiuchi, 2006), to modeling based on physical principles (Gheissari and Bab-Hadiashar, 2003). The primary Gheissari and Bab-Hadiashar, 2003).…”
mentioning
confidence: 99%
“…In color segmentation of an image, the objective is to spatially separate regions based on similarities inside each region and differences among distinct regions. The way to undertake the segmentation of color varies from the empirical evaluation of various color spaces (Horiuchi, 2006), to modeling based on physical principles (Gheissari and Bab-Hadiashar, 2003). The primary Gheissari and Bab-Hadiashar, 2003).…”
mentioning
confidence: 99%
“…The luminescence L of a pixel in RGB spaced was calculated with YIQ system [13] given by eq. (1).The luminance of a gray scale image pixel contains sufficient information to represent it into its parallel color space and provides extra viscous measures and perceivable variability within the object (local) and in the entire image (global) as shown in Figure 2.…”
Section: Methodsmentioning
confidence: 99%
“…There is thus a need to explore alternate segmentation methodologies. Specifically, colorized segmentation of gray scale images may yield enhanced results compared to naked eye assessment of normal and diseased tissue based on monochrome data [13] , [14] .…”
Section: Introductionmentioning
confidence: 99%
“…The way to undertake the segmentation of color varies from the empirical evaluation of various color spaces (Horiuchi, 2006), to modeling based on physical principles (Gheissari and Bab-Hadiashar, 2003). The primary Gheissari and Bab-Hadiashar, 2003).…”
Section: Location and Classification Of Moving Fruitsmentioning
confidence: 99%