• Proceedings of the Korea Society of Costume Conference
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• 2001.08a
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• pp.53-55
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• 2001

No Abstract, See Full-text

• Proceedings of the Korea Society of Costume Conference
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• 2001.08a
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• pp.68-71
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• 2001

No Abstract, See Full-text

• Proceedings of the KSEEG Conference
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• 2007.04a
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• pp.201-204
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• 2007

See Full Text

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.17-24
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• 2000

The Joint Photographic Experts Group (JPEG) is a standara still-image compression technique, established by the International for Standardization (ISO) and International Telecommunication Standardization Sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are nto the same as values before compression. Image of JPEG compression is often made to JPEG recompression at saving to apply JPEG compression of color image. In general, JPEG is a lossy compression and compression image is predicted to be varied image quality according to recompressed Q-factor. Various distortions of JPEG compression and JPEG recompression has been reported in previous paper. In this paper, we compress four difference color samples (photo image, gradient image, vector drawing image, text image) according to various Q-factor, and then compressed images are recompressed according to various Q-factor once again. As the results, we inspect variation of quality and file size of recompressed color image, and ensure the optimum recompression factor.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.856-868
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• 2007

We propose an effective method for block classification in a document image. The gray level document image is converted to the binary image for a block segmentation. This binary image would be smoothed to find the locations and sizes of each block. And especially during this smoothing, the inner block heights of each block are obtained. The gray level image is divided to several blocks by these location informations. The SGLDM(spatial gray level dependence matrices) are made using the each gray-level document block and the seven second-order statistical texture features are extracted from the (0,1) direction's SGLDM which include the document attributes. Document image blocks are classified to two groups, text and non-text group, by the inner block height of the block at the nearest neighbor rule. The seven texture features(that were extracted from the SGLDM) are used for the five detail categories of small font, large font, table, graphic and photo blocks. These document blocks are available not only for structure analysis of document recognition but also the various applied area.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.591-600
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• 2006

This paper describes the development and implementation of a algorithm to decompose word images from image regions mixed text/graphics in document images using statistical analyses. To decompose word images from image regions, the character components need to be separated from graphic components. For this process, we propose a method to separate them with an analysis of box-plot using a statistics of structural components. An accuracy of this method is not sensitive to the changes of images because the criterion of separation is defined by the statistics of components. And then the character regions are determined by analyzing a local crowdedness of the separated character components. finally, we devide the character regions into text lines and word images using projection profile analysis, gap clustering, special symbol detection, etc. The proposed system could reduce the influence resulted from the changes of images because it uses the criterion based on the statistics of image regions. Also, we made an experiment with the proposed method in document image processing system for keyword spotting and showed the necessity of studying for the proposed method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.153-166
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• 2008

According to the growth of the internet and the usage of software agents, the CAPTCHA that is a method for taking apart humans and computers has been widely deployed and used. As the results of many research activities, the CAPTCHA, which is spoken for a distorted image material including random text, has known to be easily breakable via artificial intelligence techniques. As one of alternatives for those text-based CAPTCHAs, methods using photos are concerned and various image-based CAPTCHAs are suggested. However, image-based CAPTCHAs still have some problems. In this paper, we discuss what are the problems in each image-based CAPTCHA and propose a new image-based CAPTCHA using image composition as the solution of those problems. Furthermore, for the secure operation of the CAPTCHA, we suggest a communication protocol that works without the virtual session and consider possible security and usability problems in the protocol.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.2
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• pp.55-68
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• 2000

Joint photographic experts group (JPEG) is a standard still-image compression technique, established by the international organization for standardization (ISO) and international telecommunication standardization sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are not the same as the value before compression. Various distortions of JPEG compression and JPEG recompression has been reported in various papers. The Image compressed by JPEG is often recompressed by same type compression method in JPEG. In general, JPEG is a lossy compression and the quality of compressed image is predicted that is varied in according to recompression Q-factor. In this paper, four difference color samples(photo image, gradient image, gradient image, vector drawing image, text image) were compressed in according to various Q-factor, and then the compressed images were recompressed according to various Q-factor once again. As the result, this paper evaluate the variation of image quality and file size in JPEG recompression and recommed the optimum recompression factor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2312-2325
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• 2013

In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1135-1140
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• 2007

This paper proposes an edge-based text region detection algorithm using the adaptive character-edge maps which are independent of the size of characters and the orientation of character string in natural images. First, labeled images are obtained from edge images and in order to search for characters, adaptive character-edge maps by way grammar are applied to labeled images. Next, selected label images are clustered as for distance of its neighbors. And then, text region candidates are obtained. Finally, text region candidates are verified by using the empirical rules and horizontal/vertical projection profiles based on the orientation of text region. As the results of experiments, a text region detection algorithm turned out to be robust in the matter of various character size, orientation, and the complexity of the background.