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In printed stylized documents, text lines may be curved in shape and as a result characters of a single line may be multi-oriented. This paper presents a multi-scale and multi-oriented character recognition scheme using foreground as well as background information. Here each character is partitioned into multiple circular zones. For each zone, three centroids are computed by grouping the constituent...
Recognizing text in historical maps is inherently difficult due to input challenges such as artifacts interfering with the text or an unpredictable rotation and orientation of the text. This paper discusses our algorithm that overcomes the limitations of the input by adding extra input consisting of multiple layers of images of the same map area but across different time periods and names of geographic...
The authors have conducted studies on recognizing Arabic news captions to develop a system for video retrieval to index and edit Arabic broadcast programs daily received and stored in big database. This paper describes a dedicated OCR for recognizing low resolution news captions in video images. News caption recognition system consisting of text line extraction, word segmentation and segmentation-recognition...
Natural scene text recognition has proved to be challenging due to the unconstrained wild conditions. In this paper, to solve this problem we propose a method which first detects and recognizes characters by utilizing the high performance Convolutional Neural Network (CNN). Then for post-processing, inspired by its success in speech recognition, we employ the efficient and flexible Weight Finite State...
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