Abstract
In this paper an evaluation of the influence of luminance L* at the L*a*b* color space during color segmentation is presented. A comparative study is made between the behavior of segmentation in color images using only the Euclidean metric of a* and b* and an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results is obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume.
Highlights
Image segmentation consists of partitioning an entire image into different regions, which are similar in some predefined manner
The manner in which the tests were implemented is as follows: In the case of the L*a*b* color space, the RGB image was previously transformed to L*a*b* color space discarding in all cases the luminance L* in order to calculate the Euclidean distance on the planes a*b* independently of the illumination
Hue was selected as the parameter because its change integrates the three RGB color channels together, making it more difficult to be processed by extending grayscale techniques to each color channel, forcing the segmentation algorithms in evaluation to use the color information holistically
Summary
Image segmentation consists of partitioning an entire image into different regions, which are similar in some predefined manner. It is an important and difficult task in image analysis and processing. Hue was selected as the parameter because its change integrates the three RGB color channels together, making it more difficult to be processed by extending grayscale techniques to each color channel, forcing the segmentation algorithms in evaluation to use the color information holistically. Samples of pixels corresponding to the figure were obtained by two squares of 2 × 2 pixels starting at the pixel (84, 84) and (150, 150). Samples for background pixels were obtained by two squares of 2 × 2 pixels starting at pixel (15, 15) and (150, 180)
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