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What is Image Thresholding

Handbook of Research on Swarm Intelligence in Engineering
It is a popular tool of image segmentation used to distinguish objects from its background in any gray level image.
Published in Chapter:
Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey
Sandip Dey (Camellia Institute of Technology, India), Siddhartha Bhattacharyya (RCC Institute of Information Technology, India), and Ujjwal Maulik (Jadavpur University, India)
Copyright: © 2015 |Pages: 39
DOI: 10.4018/978-1-4666-8291-7.ch001
Abstract
In this chapter, an exhaustive survey of quantum behaved techniques on swarm intelligent is presented. The techniques have been categorized into different classes, and in conclusion, a comparison is made according to the benefits of the approaches taken for review. The above-mentioned techniques are classified based on the information they exploit, for instance, neural network related, meta-heuristic and evolutionary algorithm related, and other distinguished approaches are considered. Neural Network-Based Approaches exhibit a few brain-like activities, which are programmatically complicated, for instance, learning, optimization, etc. Meta-Heuristic Approaches update solution generation-wise for optimization, and the approaches differ based on the problem definition.
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Optimum Gray Level Image Thresholding using a Quantum Inspired Genetic Algorithm
It bifurcate an objects and its corresponding background in a gray level image.
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