DocumentCode :
2709969
Title :
A new method to generate color texture images based on HSV and olfactory system bionic model
Author :
Jin, Zhang ; Shang-wu, Zhu ; Wang Ru-long ; Guang, Li ; Freeman, Walter J.
Author_Institution :
Sch. of Software, Hunan Univ., Changsha, China
fYear :
2009
fDate :
14-19 June 2009
Firstpage :
1446
Lastpage :
1449
Abstract :
A new method to generate color texture images is proposed in this paper, which derived from our previous works to generate the gray texture. The method is based on the olfactory system bionic model to generate the gray texture. The model architecture mimics that of mammal olfactory neural system. Period function is used as the activity function of nodes in the model to realize the periodic repetition of texture. Chaotic mapping is used to adjust the model parameters to assure the model being in non-convergence state. The previous input is introduced as the noise to simulate the background noise of neural system. One color image is used as seed image. In HSV space, the Hue (H), saturation (S) and value (V) of each pixel is used as the model input and the model output is composed as the H, S and V of corresponding pixel in generated texture. Experimental results show that the proposed method can generate many beautiful color textures, whose textures are different from the original texture.
Keywords :
biocybernetics; chaos; image colour analysis; image texture; neural nets; HSV space; chaotic mapping; color texture images; gray texture image; mammal olfactory neural system; olfactory system bionic model; period function; seed image; Background noise; Chaos; Colored noise; Educational institutions; Image generation; Nerve fibers; Neural networks; Olfactory; Solid modeling; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
ISSN :
1098-7576
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2009.5178807
Filename :
5178807
Link To Document :
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