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Feature Extraction for Image Classification and Analysis with Ant Colony Optimization Using Fuzzy Logic Approach

Author(s): Subba Rao Katteda | Dr.C Naga Raju | Maddala Lakshmi Bai

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 2;
Issue: 4;
Start page: 137;
Date: 2012;
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Keywords: Ant Colony Optimization (ACO) | Fuzzy Logic | Segmentation | Classification | Analysis

The problem of structure extraction from the image which contains many clustered objects is a challengingone for high level image analysis. When an image contains many clustered objects overlapping of objectscan cause for hiding the structure. The existing segmentation techniques for better understanding, not ableto the address the constituent parts of the image implicitly. The approaches like multistage segmentationaddress to some extent, but for each stage a separate structure is extracted, and thus causes for theambiguity about the structure. The proposed approach called Ant Colony Optimization and Fuzzy logicbased technique resolves this problem, and gives the implicit structure, that meets with original structure.The segmentation approach uses the swarm intelligence technique based on the behavior of the antcolonies. The segmentation is the process of separating the non-overlapping regions that constitute animage. The segmentation is important for structured and non-structured image analysis and classificationfor better understanding
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