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Optical Character Recognition (OCR) converts images of handwritten or printed text captured by camera or scanner into editable text. OCR has seen limited adoption in mobile platforms due to the performance constraints of these systems. Intel® Atom™ processors have enabled general purpose applications to be executed on handheld devices. In this paper, we analyze a reference implementation of the OCR...
An automatic recognition method for steel billet images with different orientations is proposed in this paper. A crucial part of this method is to segment the image firstly, and then use the projection features of the segmented image to distinguish the different orientations of the steel billet in production line. After the string is segmented into individual characters, the segmented characters can...
Automatic Arabic handwritten text recognition is still an open research field, methods that describe satisfactory solution are still lacking. This can be attributed to cursive orthography and to the letter shape context sensitivity, which complex the problem of the character segmentation. This paper presents a heuristic rule based analytical segmentation approach for handwritten Arabic text, which...
Text in video frames contains high-level semantic information and thus can contribute significantly to video content analysis and retrieval. Therefore, video text recognition is crucial to the research in all video indexing and summarization. In the processing of video text recognition, in the extraction step, background in the text rows is removed so only the text pixels are left for recognition...
Document image has been the area of research for a couple of decades because of its potential application in the area of text recognition, line recognition or any other shape recognition from the image. Text recognition from document image is very much dependent on the language of the text itself. English text recognition algorithms have already been developed and are standardized. Some works on Bangla...
We propose a fully automatic method for summarizing and indexing unstructured presentation videos based on text extracted from the projected slides. We use changes of text in the slides as a means to segment the video into semantic shots. Unlike precedent approaches, our method does not depend on availability of the electronic source of the slides, but rather extracts and recognizes the text directly...
Character segmentation and recognition are two difficult key steps in extracting literal information from images. This paper proposes a method for effective segmentation and recognition of characters in complicated graphical contexts of line drawings. Text pixels are first separated from intersecting non-text objects with the holistic graphic recognition algorithm, and then character boxes are grouped...
A new approach to Thai font type recognition that is presented in this paper is based on linear interpolation analysis of the character contour. The algorithm can perform effectively and classify font type obviously. The same font type show high similarity coefficient which is 83.95 but the different font types is below 35.54.
This paper proposes a new approach for the multiple frame integration of video, whose novelty mainly lies in three phases: Firstly, in the text-block group (TBG) identification, we identify the blocks with the same text by considering jointly the location, edge distribution and contrast of the text block. Then, in the TBG filtering, to avoid the bad effects of the blurred text on the result of integration,...
We propose a combined character separation and recognition approach for low-resolution images of alphanumeric text. By synthesising the image formation process a set of low-resolution templates is created for each character. Cluster algorithms and normalised cross-correlation are then applied to match these templates and thereby allowing both character separation and recognition to be achieved at...
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