Automatic and Efficient Cleansing of Illustration Images in Web

REVATHY S, SUGANYADEVI SRV, SUPRIYAA D, PRIYADHARSINI R, MANISHA S

Abstract


The scope and nature of image data is crucial to understand and to determine the complexity of image search design. Interest in image retrieval has increased in large due to the rapid growth of the World Wide Web. There are huge number of high quality images for different image category available in web. When a search query is given, the information retrieval system gives us both relevant and irrelevant images to the users. In order to satisfy the requirement of the user and to give relevant details, there are many interactive and automatic methods that exists. The interactive methods are capable of building large collection of images with ground truth labels, but they depend heavily on human efforts. While Automatic methods leverage an object category model trained on text and visual features. The objective of this work is to review the works both interactive and automatic methods proposed for generating a large number of images for a specified object class.


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