Content Based Image Retrieval Based On Internal Regions Using Clustering Methods in Interactive Genetic Algorithm
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 2
Abstract
Content Based Image Retrieval (CBIR) is a way to extend and improve query methods for searching the image in databases. In CBIR, a description of the required content in terms of visual features of an image is required. Images can then be ranked with respect to their similarity to the description. Extracting required textual information manually or automatically has been a relatively simple task. However, when the information is held as an image, the same is a hard task. Though, the human can interpret and teach the characteristics of the image to a machine are possible. The Proposed work focuses on two methods: 1) Interactive Genetic Algorithm and 2) Image Features. In IGA the search process is repeated until the user satisfies with the result. The image features is of color, edge and texture descriptor. This is done by using the low-level descriptions. Index Terms—Content-based image retrieval (CBIR), human– machine interaction, interactive Genetic Algorithm (GA) (IGA), low-level descriptors.
Authors and Affiliations
G. Barani, K. M. Kirthika, V. R. Meenachi, K. Senthamarai
Keywords
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