Surekha Chandran

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Image content clustering is an effective way to organize large databases thereby making the content based image retrieval process much easier. However, clustering of images with varied background and foreground is quite challenging. In this paper, we propose a novel image content clustering paradigm suitable for clustering large and diverse image databases.(More)
The advancements in the field of internet and cloud computing has resulted in a huge amount of multimedia data and processing of this data have become more complex and computationally intensive. As a result, it has become very challenging for image retrieval algorithms to efficiently extract useful information from these data. Local Derivative Pattern (LDP)(More)
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