论文信息 - Color Image Segmentation Using Soft Computing

Color Image Segmentation Using Soft Computing

segmentation is an important process and are used in in many image processing applications. Color images can increase the quality of segmentation but also increases the complexity of the problem. To reduce this complexity soft computing tools played promising role. This paper discussed the segmenting any given color image using soft computing approaches i.e. fuzzy logic, neural network and genetic algorithms.

V. K. Banga | Navkirat Kaur

[1] B. Sheela Rani,et al. Colour image segmentation using fuzzy clustering techniques and competitive neural network , 2011, Appl. Soft Comput..

[2] CATALIN AMZA,et al. A REVIEW ON NEURAL NETWORK-BASED IMAGE SEGMENTATION TECHNIQUES , 2000 .

[3] Marco Gallotta,et al. Genetic Algorithms: Colour Image Segmentation Literature Review , 2007 .

[4] Wilhelm Burger,et al. Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[5] P. Chainais,et al. Segmentation of EIT images using fuzzy clustering. A preliminary study , 2005 .

[6] G. Padmavathi,et al. Non linear Image segmentation using fuzzy c means clustering method with thresholding for underwater images , 2010 .

[7] Gour C. Karmakar,et al. Object Based Image Segmentation Using Fuzzy Clustering , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[8] Dr. P. R. Bajaj,et al. Fuzzy based Color Image Segmentation using Comprehensive Learning Particle Swarm Optimization ( CLPSO ) – A Design Approach , 2022 .