Color image simplification by morphological hierarchical segmentation and color clustering

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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Model of the quasi-optimal hierarchical segmentation of a color image

Journal of Optical Technology ◽

10.1364/jot.82.000425 ◽

2015 ◽

Vol 82 (7) ◽

pp. 425 ◽

Cited By ~ 3

Author(s):

M. V. Kharinov

Keyword(s):

Color Image ◽

Hierarchical Segmentation

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Color Image Information Hiding Based on Perceptual Color Clustering

2010 International Conference on Computational Intelligence and Software Engineering ◽

10.1109/wicom.2010.5601277 ◽

2010 ◽

Cited By ~ 1

Author(s):

Li Jiang ◽

Zheng-quan Xu

Keyword(s):

Information Hiding ◽

Color Image ◽

Image Information ◽

Color Clustering

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ROBUST IMAGE RETRIEVAL APPROACH BASED ON CLUSTERING ANALYSIS OF RE-QUANTIZED COLOR IMAGE

International Journal of Wavelets Multiresolution and Information Processing ◽

10.1142/s0219691307001720 ◽

2007 ◽

Vol 05 (01) ◽

pp. 213-225 ◽

Cited By ~ 3

Author(s):

YA-LI JI ◽

XIAO-PING CHENG ◽

NAI-QIN FENG

Keyword(s):

Image Retrieval ◽

Color Image ◽

Color Space ◽

Feature Representation ◽

Hsv Color Space ◽

Invariant Moments ◽

Robust Image ◽

Color Clustering ◽

Object Features ◽

Large Image Databases

In this paper, we propose a robust approach about color image retrieval. It can realize fast matching in CBIR (Content-Based Image Retrieval) when we search in large image databases. Indexes root in object features of Z image which is the result of re-quantization in HSV color space, matching with a non-geometrical distance is based on objects, so time consumption pixel by pixel can be avoided. Because Z image is made up of many color clustering regions and invariant moments are used for feature representation, our approach is robust to translation, scale and rotation.

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