Anurag Bhardwaj

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We present a new feature representation method for scene text recognition problem, particularly focusing on improving scene character recognition. Many existing methods rely on Histogram of Oriented Gradient (HOG) or part-based models, which do not span the feature space well for characters in natural scene images, especially given large variation in fonts(More)
Many feature extraction approaches for off-line handwriting recognition (OHR) rely on accurate binarization of gray-level images. However, high-quality binarization of most real-world documents is extremely difficult due to varying characteristics of noises artifacts common in such documents. Unlike most of these features, Gabor features do not require(More)
With the rapid proliferation of smartphones and tablet computers, search has moved beyond text to other modalities like images and voice. For many applications like Fashion, visual search offers a compelling interface that can capture stylistic visual elements beyond color and pattern that cannot be as easily described using text. However, extracting and(More)
Keyword retrieval in handwritten document images (word spotting) is very challenging given that OCR accuracy is not yet adequate for handwritten scripts, specially with large lexicons. Various proposed approaches build indices on information such as image features or OCR scores and have improved the performance of the traditional approach that builds index(More)
The paper attempts to create a handwritten document retrieval system suitable for Tamil language, with a view to record traditional literature content for future reference. It projects a search mechanism to access the query word images using a statistical model based methodology. The scheme revolves around a well defined procedure which results in word(More)
With the ever-increasing growth of the World Wide Web, there is an urgent need for an efficient information retrieval system that can search and retrieve handwritten documents when presented with user queries. However, unconstrained handwriting recognition remains a challenging task with inadequate performance thus proving to be a major hurdle in providing(More)
We present a novel compact image descriptor for large scale image search. Our proposed descriptor Geometric VLAD (gVLAD) is an extension of VLAD (Vector of Locally Aggregated Descriptors) that incorporates weak geometry information into the VLAD framework. The proposed geometry cues are derived as a membership function over keypoint angles which contain(More)
This paper describes a method for script independent word spotting in multilingual handwritten and machine printed documents. The system accepts a query in the form of text from the user and returns a ranked list of word images from document image corpus based on similarity with the query word. The system is divided into two main components. The first(More)
Despite several decades of research in document analysis, recognition of unconstrained handwritten documents is still considered a challenging task. Previous research in this area has shown that word recognizers produce reasonably clean output when used with a restricted lexicon. But in absence of such a restricted lexicon, the output of an unconstrained(More)