Modelling and segmentation of colour images in polar representations

被引:49
作者
Angulo, Jesus
Serra, Jean
机构
[1] Ecole Mines Paris, Ctr Morphol Math, F-77300 Fontainebleau, France
[2] ESIEE, Lab A2SI, F-93162 Noisy Le Grand, France
关键词
colour mathematical morphology; colour segmentation; saturation; norms; bi-variate histograms; jump connection;
D O I
10.1016/j.imavis.2006.07.018
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The suitability of polar representation for quantitative image processing tasks is investigated. The classical colour polar-based representations (HLS, HSV, etc.) lead to brightness and saturation with nonconsistent properties. After a short critical analysis of the gamma correction, a new polar representation using the L-1 norm is proposed. It satisfies several quantitative requirements. The relevance of this representation is demonstrated by means of luminance/saturation histograms, which exhibit typical alignments. Their physical interpretation leads to a model for light reception in terms of linearly regionalized spectra. A full example illustrates the application of the histogram approach. Colour images are multivariable functions, and for segmenting them one must go through a reducing step. It is classically obtained by calculating a gradient module, which is then segmented as a grey tone image. An alternative solution is proposed. It is based on separated segmentations, followed by a final merging into a unique partition. The generalisation of the top-hat transformation for extracting colour details is also considered. These new marginal colour operators take advantage of an adaptive combination of the chromatic and the achromatic (or the spectral and the spatio-geometric) colour components. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:475 / 495
页数:21
相关论文
共 53 条
[1]  
Angulo J., 2004, Traitement du Signal, V21, P583
[2]  
Angulo J, 2005, COMPUT IMAGING VIS, V30, P387
[3]  
Angulo J, 2003, 2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 2, PROCEEDINGS, P125
[4]  
ANGULO J, 2003, THESIS ECOLE MINES P
[5]  
ANGULO J, 2003, O INT WORKSH SEM PRO, P59
[6]  
[Anonymous], 1998, P 4 INT S MATH MORPH
[7]   Spectral gradients for color-based object recognition and indexing [J].
Berwick, D ;
Lee, SW .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2004, 94 (1-3) :28-43
[8]  
BEUCHER S, 1992, P ISMM 94 KLUW 1994, P433
[9]  
C.I.E. (Commission Internationale de L'Eclairage), 1986, COLORIMETRY
[10]  
CARRON T, 1994, IEEE IMAGE PROC, P977, DOI 10.1109/ICIP.1994.413699