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Abstract
Based Image Retrieval (CBIR) is a method of extracting image features and calculate visual similarity based on these features. Lot of research activity is continuing for optimizing and improving the feature extraction methods focusing on colour, texture and shape features to minimize the semantic gap. Relevant Feedback (RF) is one variant of CBIR wherein the user provides feedback by selecting the most relevant image from retrieved images and make it a query image for the subsequent iterations. The RF methods improved the performance of the overall system in multiple iterations but the time taken for the total process increases on the other hand. This paper attempts to address the semantic gap problem by having the user interface in the forward path by adding some more key requirements of the user for narrowing down the search options thereby increasing the system performance and reducing the retrieval time.
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