Titlebook: Hybrid Soft Computing for Multilevel Image and Data Segmentation; Sourav De,Siddhartha Bhattacharyya,Paramartha Dutt Book 2016 Springer In

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Image Segmentation: A Review,This chapter intends to provide a brief review of different image segmentation techniques.

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Self-supervised Grey Level Image Segmentation Using an Optimised MUSIG (OptiMUSIG) Activation FunctDifferent types of image segmentation methods, both supervised and unsupervised, as discussed in Chap.?., have been applied over the years for the purpose of image segmentation and extraction.

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Self-supervised Colour Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation FunctColour image segmentation and analysis form a challenging proposition in the image processing arena owing to the nature and variety of data to be processed?[258, 259].

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Self-supervised Grey Level Image Segmentation Using Multi-Objective-Based Optimised MUSIG (OptiMUSIThe multilevel greyscale image can efficiently be segmented by the OptiMUSIG activation function with the help of the multilayer self-organizing neural network (MLSONN) architecture.

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Self-supervised Colour Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaIn Chap.?., it has been illustrated and proved that the colour images are efficiently segmented by the ParaOptiMUSIG [193, 258, 273] activation function in connection with the parallel self-organizing neural network (PSONN) [195, 196] architecture.

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Book 2016omputing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures..This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering,