Image retrieval using hypergraph of visual concepts
Автор: Sandhya V. Kawale, S. M. Kamalapur
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 12 Vol. 9, 2017 года.
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Retrieving images similar to query image from a large image collection is a challenging task. Image retrieval is most useful in the image search engine to find images similar to the query image. Most of the existing graph based image retrieval methods capture only pair-wise similarity between images. The proposed work uses the hypergraph approach of the visual concepts. Each image can be represented by combination of the several visual concepts. Visual concept is the specific object or part of an image. There are several images in the database which can share multiple visual concepts. To capture such a relationship between group of images hypergraph is used. In proposed work, each image is considered as a vertex and each visual concept as a hyperedge in a hypergraph. All the images sharing same visual concept, form a hyperedge. Images in the dataset are represented using hypergraph. For each query image visual concept is identified. Similarity between query image and database image is identified. According to these similarities association scores are assigned to images, which will handle the image retrieval.
Clustering, Hypergraph, Image Retrieval, Ranking, Visual Concepts
Короткий адрес: https://sciup.org/15016217
IDR: 15016217 | DOI: 10.5815/ijitcs.2017.12.05
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