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Content Based Image Retrieval Using Machine Learning Technique


Author(s):

Charulata Leuva , Gujarat Technological University

Keywords:

Image Retrieval, Content Based Image Retrieval, Semantic Gap,Relevance Feedback, Support Vector Machine, Gabor Filtering

Abstract:

The fast growth of computer technologies and the coming of the World Wide Web have increased the amount and the complex difficulty of combining video, sound, words and pictures together information. A Content Based Image Retrieval (CBIR) system has been developed as an efficient image retrieval tool where by the user can provide their question to the system to allow it to retrieve the user’s desired image from the image collection. However the usual relevance responses to something or helpful returned information method to support the user question based on the representative image selection and weight ranking of the images retrieved. The Support Vector Machine(SVM) has been used to support the learning process to reduce the semantic gap between the user and the CBIR system.SVM can classify the data into relevance training set and Gabor Filtering will extract the feature from the given image dataset. It can also improve the performance of CBIR. Also solve the imbalance training set.


Other Details:

Manuscript Id :IJSTEV1I12060
Published in :Volume : 1, Issue : 12
Publication Date: 01/07/2015
Page(s): 166-171
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