Filtering color images in the xyY color space

Author(s):  
L. Lucchese ◽  
S.K. Mitra
Keyword(s):  
2015 ◽  
Vol 102 (1) ◽  
pp. 21-31
Author(s):  
Rodolfo Alvarado-Cervantes ◽  
Edgardo M. Felipe-Riveron ◽  
Vladislav Khartchenko ◽  
Oleksiy Pogrebnyak

Author(s):  
Sumitra Kisan ◽  
Sarojananda Mishra ◽  
Ajay Chawda ◽  
Sanjay Nayak

This article describes how the term fractal dimension (FD) plays a vital role in fractal geometry. It is a degree that distinguishes the complexity and the irregularity of fractals, denoting the amount of space filled up. There are many procedures to evaluate the dimension for fractal surfaces, like box count, differential box count, and the improved differential box count method. These methods are basically used for grey scale images. The authors' objective in this article is to estimate the fractal dimension of color images using different color models. The authors have proposed a novel method for the estimation in CMY and HSV color spaces. In order to achieve the result, they performed test operation by taking number of color images in RGB color space. The authors have presented their experimental results and discussed the issues that characterize the approach. At the end, the authors have concluded the article with the analysis of calculated FDs for images with different color space.


2014 ◽  
Vol 23 (3) ◽  
pp. 033009 ◽  
Author(s):  
Suwat Tachaphetpiboon ◽  
Kharittha Thongkor ◽  
Thumrongrat Amornraksa ◽  
Edward J. Delp

2010 ◽  
Vol 26-28 ◽  
pp. 48-54
Author(s):  
Jin Ling Wei ◽  
Jun Meng ◽  
Wei Song

According to the analysis of every feature element’s grey images in RGB color space and HSI color space, each of the elements represents different information of the color image. From the analysis of the Histogram of color images, the value range of hue H basically keeps stable, which is proved by experiments to be the most stable and representative one. Finally we illustrated by application instances that the method of recognition and tracking of the objective moving robot based on hue character H is applicable.


2011 ◽  
Vol 474-476 ◽  
pp. 2140-2145
Author(s):  
Si Li ◽  
Hong E Ren

Combined with the composition characteristics of forest fire image background when the forest fire occurred during different time periods of night and day, different image segmentation methods were applied to the forest fire color images of different time periods respectively, which could improve the efficiency of image processing. Meanwhile, application of H and S components from HSV color space, the strategy on color image segmentation which processed the segmentation processing to forest fire color images with complicated background was proposed combined with Otsu algorithm. The results of simulation experiment showed that the above-mentioned segmentation methods were obtained satisfactory segmentation effects when the segmentation on forest fire color images during different time periods of night and day were processed respectively. And also application of Otsu algorithm based on HSV color model, the forest fire image segmentation occurred in the daytime was processed, which overcame the interference factors of light and smoke, as well as the shortage of noise sensibility due to Otsu algorithm.


Author(s):  
JESÚS ANGULO

This paper deals with color image simplification using levelings. This class of connected filters suppresses details but preserves the contours of the remaining structures or objects. As the notion of "color structure" is not trivial, the formulation of morphological operators for color images involves many open issues. The principle choice of a well-defined color space is crucial and it is proposed to work on a luminance/saturation/hue representation defined by the norm L1. A family of morphological color operators is then introduced using the classical formulation with total orderings by means of lexicographic cascades. In this framework, a methodology for color image simplification is introduced, which takes advantage of a saturation-controlled combination of the chromatic and the achromatic (or the spectral and the spatio-geometric) components. More precisely, it is based on the application of a color leveling to each significant region, specifically adapted to the nature (chromatic/achromatic) of the region and which needs an initial image partition into the homogenous regions. Experimental results illustrate the performance of the new developed algorithms.


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