• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.18-26
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• 2015

Geometric distortion and shadow effect due to capturing angle could be included in document copy images that are captured by a camera in stead of a scanner. In this paper, a clean black and white document image generation algorithm by distortion correction and shadow elimination based on a camera, is proposed. In order to correct geometric distortion such as straightening un-straight boundary lines occurred by camera lens radial distortion and eliminating outlying area included by camera direction, second derivative filter based document boundary detection method is developed. Black and white images have been generated by adaptive binarization method by eliminating shadow effect. Experimental results of the black and white document image generation algorithm by recovering geometrical distortion and eliminating shadow effect for the document images captured by smart phone camera, shows very good processing results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.680-686
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• 2006

Document images captured by scanners have only skewing distortion. But camera captured document images have not only skew but also vignetting effect and geometric distortion. Vignetting effect, which makes the border areas to be darker than the center of the image, make it difficult to separate characters from the document images. But this effect has being decreased, as the lens manufacturing skill is developed. Geometric distortion, occurred by the mismatch of angle and center position between the document image and the camera, make the shape of characters to be distorted, so that the character recognition is more difficult than the case of using scanner. In this paper, we propose a method that can increase the performance of character recognition by correcting the geometric distortion of document images using a linear approximation which changes the quadrilateral region to the rectangle one. The proposed method also determine the quadrilateral transform region automatically, using the alignment of character lines and the skewed angles of characters located in the edges of each character line. Proposed method, therefore, can correct the geometric distortion without getting positional information from camera.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.143-150
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• 2005

Camera image is very sensitive to illumination that result in difficulties for recognizing character. Also Camera captured document images have not only skew but also vignetting effect and geometric distortion. Vignetting effect make it difficult to separate characters from the document images. Geometric distortion, occurred by the mismatch of angle and center position between the document image and the camera, make the shape of characters to be distorted, so that the character recognition is more difficult than the case of using scanner. In this paper, we propose a method that can increase the performance of character recognition by correcting the geometric distortion of document images using a linear approximation which changes the quadrilateral region to the rectangle one. The proposed method also determine the quadrilateral transform region automatically, using the alignment of character lines and the skewed angles of characters located in the edges of each character line. Proposed method, therefore, can correct the geometric distortion without getting positional information from camera.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.239-240
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• 2013

The quality of document images captured by digital camera might be degraded because of non-uniform illumination condition. The high illumination (glare distortion) affects on the contrast condition of the document images. This condition leads to the poor contrast condition of the text in document image. So, optical character recognition (OCR) system might hardly recognize text in the high illuminated area. The method to increase the contrast condition between text (foreground) and background in high illuminated area is proposed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.556-563
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• 2006

We should extract lines and data which consist of the table in order to classify the table region and analyze its structure in document image. But it is difficult to extract lines and data exactly because the lines are cut and their lengths are changed, or characters or noises are merged to the table lines. These problems result from the error of image input device or image reduction. In this paper, we propose the better method of extracting lines and data for table region classification and structure analysis than the previous ones including commercial softwares. The prposed method extracts horizontal and vertical lines which consist of the table by the use of one dimensional median filter. This filter not only eliminates the noises which attach to the line and the lines which are orthogonal to the filtering direction, but also connects the cut line of which the gap is shorter than the length of the filter tap in the process of extracting lines to the filtering direction. Furthermore, texts attached to the line are separated in the process of extracting vertical lines. This is an example of ABSTRACT format.

• International Journal of Contents
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• v.10 no.4
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• pp.63-68
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• 2014

In this paper, we propose a smart system that can optically recognize a music score within a document and can play the music after recognition. Many historic handwritten documents have now been digitalized. Converting images of a music score within documents into digital files is particularly difficult and requires considerable resources because a music score consists of a 2D structure with both staff lines and symbols. The proposed system takes an input image using a mobile device equipped with a camera module, and the image is optimized via preprocessing. Binarization, music sheet correction, staff line recognition, vertical line detection, note recognition, and symbol recognition processing are then applied, and a music file is generated in an XML format. The Music XML file is recorded as digital information, and based on that file, we can modify the result, logically correct errors, and finally generate a MIDI file. Our system reduces misrecognition, and a wider range of music score can be recognized because we have implemented distortion correction and vertical line detection. We show that the proposed method is practical, and that is has potential for wide application through an experiment with a variety of music scores.