Now-a-days, the video recording technologies have turned out to be more and forceful easier utilize. Therefore, numerous universities are publishing their lectures online in order make them reachable for learners or students. These lecture videos encapsulate handwritten text written either on a paper blackboard tablet using stylus. On other hand, this mechanism of consumes huge quantity multime...

Deep learning has yielded promising results for medical image diagnosis but relies heavily on manual annotations, which are expensive to acquire. We present Cross-DL, a cross-modality framework intracranial abnormality detection and localization in head computed tomography (CT) scans by from free-text imaging reports. Cross-DL discretizer that automatically extracts discrete labels of types loc...

We show how to exploit temporal and spatial coherence to achieve efficient and effective text detection and decoding for a sensor suite moving through an environment in which text occurs at a variety of locations, scales and orientations with respect to the observer. Our method uses simultaneous localization and mapping (SLAM) to extract planar “tiles” representing scene surfaces. It then fuses...

Text binarisation process classifies individual pixels as text or background in the textual images. Binarization is necessary to bridge the gap between localization and recognition by OCR. This paper presents Sliding window method to binarise text from textual images with textured background. Suitable preprocessing techniques are applied first to increase the contrast of the image and blur the ...

Automatic character detection in video sequences is a complex task, due to the variety of sizes and colors as well as to the complexity of the background. In this paper we address this problem by proposing a localization/verification scheme. Candidate text regions are first localized by using a fast algorithm with a very low rejection rate, which enables the character size normalization. Contra...

Latent Dirichlet Allocation (LDA) is an unsupervised, statistical approach to document modeling that discovers latent semantic topics in large collections of text documents. LDA posits that words carry strong semantic information, and documents discussing similar topics will use a similar group of words. Latent topics are thus discovered by identifying groups of words in the corpus that frequen...

In this paper we describe our recent research efforts towards reliable and automatic generation of indices for use in content understanding of video. Following our earlier research in temporal shot segmentation of video, we have developed a comprehensive system framework for segmenting an unconstrained variety of text from general purpose broadcast video. In addition, the framework also contain...

The ever-increasing number of publicly available biomedical articles calls for automatic information extraction from digitized publications. We have implemented a pipeline which, by exploiting text mining and semantic technologies, helps researchers easily access semantic content of thousands of abstracts and full text articles from PubMed and Elsevier. The text mining component analyzes the ar...

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Content-based information retrieval from digital video databases and media archives is a challenging problem and is rapidly gaining widespread research and commercial interest. For a reliable retrieval and intelligent access to video programs, indexing should provide semantic descriptors. One way to include more semantic knowledge into the indexing process is to use the text embedded within ima...