This paper proposes an approach for the segmentation of color images using CIELab color space and Ant based clustering. Image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. The objective of segmentation is to change the image into meaningful form that is easier to analyze. This paper elaborat...

Compared with the planar color gamut, stereoscopic gamut is more uniform, it can reflect actual situation of display system by considering changes in brightness. In this article we introduce another advantage using external factors system, such as influence spectral reflectivity screen. When space converted from CIEXYZ to CIELAB, use a fixed white point, these results are intuitive and reasonab...

Several of the spectral match metrics considered by Imai, et al., are compared for a large number of non-metameric pairs of spectra in order to assess how accurately they track human perception as predicted by CIELAB (i.e., the extent to which the metric will exhibit a proportional relationship with CIELAB total color difference), and how precisely they do so (i.e., the relative compactness of ...

Skin Color segmentation plays an important role in various applications such as face recognition, gesture recognition, human computer interaction etc. Face recognition is of main concern in skin color segmentation. There are various color models used for skin color segmentation (YCbCr, HSV and CIELAB) but appropriate method should be used for skin color segmentation. In real time the main probl...

The Rochester Institute of Technology-Dupont dataset [Color Res. Appl. 16, 297-316 (1991)] has been used to analyze the uniformity of seven color metrics, developed after CIELUV and CIELAB, with methods similar to those previously applied to several other classical datasets [J. Opt. Soc. Am. A 9, 1247-1253 (1992)]. Significant performance improvements over CIELAB were found with several CIELAB-...

A color visual difference model (CVDM) was developed to predict the image quality difference of two images. The model is an extension of the two previously published models: The monochromatic Visible Difference Predictor (VDP) by Scott Daly and the color Spatial-CIELAB (SCIELAB) model by Zhang et al. The CVDM consists of color space conversion, modulation by contrast sensitivity functions, visu...

PURPOSE We developed a new artificial image enhancement system aimed at intraoperative visibility improvement as a clinical prototype. We examined each optical characteristic and change in intraoperative visibility using brilliant blue G (BBG) staining with various sharp cut filters (SCFs). METHOD This was a retrospective and observational study. The system was composed of several filters att...

Traditional color spaces have been widely used in a variety of applications including digital color imaging, color image quality, and color management. These spaces, however, were designed for the domain of color stimuli typically encountered with reflecting objects and image displays of such objects. This means the domain of stimuli with luminance levels from slightly above zero to that of a p...