Nowadays, Content Based Image Retrieval (CBIR) plays a significant role in the image processing field. Images relevant to a given query image are retrieved by the CBIR system utilizing either low level features (such as shape, color etc.,) or high level features (human perception). Image-based math retrieval is a new area of research which has gained importance because of the need for extracting the mathematical expressions for processing. In this paper, a method for locating mathematical expressions in document images without the use of optical character recognition is presented. Initially, when a query image is given, images relevant to it are retrieved from the image database based on its feature values. We have performed retrieval utilizing one of the evolutionary algorithms called Evolutionary Programming (EP). Subsequent to this process, query keyword which is are generally feature values is extracted from these retrieved images and then based on this query keyword, relevant images are retrieved from the database. The images retrieved based on feature values are compared and the images which are both visually and semantically identical are identified. Better results obtained by the proposed approach when it was compared to existing method for Heterogeneous document Images, it is queried using different types of images prove the efficiency of the implemented technique.
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