• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.59-68
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• 1999

In this paper, we propose an algorithm to locate the corpus callosum automatically from midsagittal brain MR images using the statistical characteristics and shape information of the corpus callosum. In the proposed algorithm, we first extract regions satisfying the statistical characteristics of the corpus callosum and then find a region matching the shape information. In order to match the shape information, a new directed window region-growing algorithm is proposed instead of using conventional contour matching algorithms. Using the proposed algorithm, we adaptively relax the statistical requirement until we find a region matching the shape information. Experiments show promising results.

• Transactions on Electrical and Electronic Materials
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• v.17 no.6
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• pp.363-368
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• 2016

Rectangular shape detection plays an important role in many image recognition systems. However, it requires continued research for its improved performance. In this study, we propose a strong rectangular shape detection algorithm, which combines the canny edge and line detection algorithms based on the perpendicularity and parallelism of a rectangle. First, we use the canny edge detection algorithm in order to obtain an image edge map. We then find the edge of the contour by using the connected component and find each edge contour from the edge map by using a DP (douglas-peucker) algorithm, and convert the contour into a polyline segment by using a DP algorithm. Each of the segments is compared with each other to calculate parallelism, whether or not the segment intersects the perpendicularity intersecting corner necessary to detect the rectangular shape. Using the perpendicularity and the parallelism, the four best line segments are selected and whether a determined the rectangular shape about the combination. According to the result of the experiment, the proposed rectangular shape detection algorithm strongly showed the size, location, direction, and color of the various objects. In addition, the proposed algorithm is applied to the license plate detecting and it wants to show the strength of the results.

• International Journal of Contents
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• v.13 no.1
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• pp.68-75
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• 2017

Interactive Typography is a process where a user communicates by interacting with text and a moving factor. This research covers interactive typography using real-time response to a user's gesture. In order to form a language-independent system, preprocessing of entered text data presents image data. This preprocessing is followed by recognizing the image data and the setting interaction points. This is done using computer vision technology such as the Harris corner detector and contour detection. User interaction is achieved using skeleton information tracked by a depth camera. By synchronizing the user's skeleton information acquired by Kinect (a depth camera,) and the typography components (interaction points), all user gestures are linked with the typography in real time. An experiment was conducted, in both English and Korean, where users showed an 81% satisfaction level using an interactive typography system where text components showed discrete movements in accordance with the users' gestures. Through this experiment, it was possible to ascertain that sensibility varied depending on the size and the speed of the text and interactive alteration. The results show that interactive typography can potentially be an accurate communication tool, and not merely a uniform text transmission system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.1-6
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• 1992

This paper proposed a neural computer architecture for the learning of script character pattern recognition categories. Oriented filter with complex cells preprocess about the input script character, abstracts contour from the character. This contour normalized and inputed to the ART. Top-down attentional and matching mechanisms are critical in self-stabilizing of the code learning process. The architecture embodies a parallel search scheme that updates itself adaptively as the learning process unfolds. After learning ART self-stabilizes, recognition time does not grow as a function of code complexity. Vigilance level shows the similarity between learned patterns and new input patterns. This character recognition system is designed to adaptable. The simulation of this system showed satisfied result in the recognition of the hand written characters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.177-180
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• 2002

Generally, it is very difficult to inspect geometric shape of large 2D objects after machining. To maintain the accuracy for inspection, a robot vision is used to divide overall shape into several enlarged images, and image processing technique is applied to acquire one minute geometric contour. The inspection is to compare the NC data with the measured contour data by the vision system, and the algorithm is to rotate to minimize the maximum deviation coinciding two geometric centers. This paper experimentally shows that the proposed inspection algorithm is very useful fur a large machined object.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.112-119
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• 2002

Generally, it is very difficult to inspect geometric shape of large 2D objects after machining. To maintain the accuracy for inspection, a robot vision is used to divide overall shape into several enlarged images, and image processing technique is applied to acquire one minute geometric contour. The inspection is to compare the NC data with the measured contour data by the vision system, and the algorithm is to rotate to minimize the maximum deviation after coinciding two geometric centers. This paper experimentally shows that the proposed algorithm is very useful for inspection of large machined objects.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.983-991
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• 1988

In this paper, a new two dimensional processing method is presented, which determines the identity, position and orientation of a part. Matching between the object and model is performed in the frequency domain. The DFT of the object contour is decomposed to estimated the orientation of the object and to evaluate the similarity between the object and model. In this context, this new approach is very rbust with respect to noise and no preprocessing of the contour is required. Also, this method has many advantages over the conventional correlation technique. With only a few uniformly sampled points, this method can estimate the accurate orientation in an efficient manner even in a noisy environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1861-1873
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• 1996

This paper describes the content-based image retrieval system that is implemented to retrieve images using constituent rate of lines and Bezier curves. We proposed the line and Bezier curve extraction algorithm which extracts lines and curve that are fitted on the contour information of images. For this extration, it was necessary to remove internal area of the proprocessed object within images and to approximate its contour to polygon, and proposed retrevial algorithm which gets the simularity using the consitituent rate of lines and curves and perform the simularity matching.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.73-85
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• 2009

This paper introduces the technique of synthesizing and evaluating human utterances with exaggerated or atypical prosody. Prosody exaggeration can be implemented by manipulating either the fundamental frequency (F0) contour, the segmental durations, or the intensity contour of an utterance. Of these three prosodic elements, two or more can be exaggerated at the same time. The algorithms of synthesis and evaluation were suggested. Learner utterances exaggerated in each of the three prosodic features were evaluated with respect to their original native versions in terms of the differences in their F0 contours, the segmental durations, and the intensity contours. The measure of differences was the Euclidean distance metric between the matching points in their F0 and intensity contours. The measure was calculated after the exaggerated learner utterances were aligned by the segments and rendered identical to their native version in terms of their segmental durations. For the evaluation of the segmental durations, no prior modifications were made in durations and the same measure was used. The results from the pilot experiment suggest the viability of this measure in the evaluation of learner utterances with atypical prosody with respect to their native versions.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.57-60
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• 2002

본 논문에서는 능동윤곽모델(active contour model)의 잘 알려져 있는 스네이크(snake) 알고리즘을 스테레오영상에 적용하여 좌 우 영상의 disparity 정보를 이용 객체의 경계선을 찾는 알고리즘을 제안한다. 스네이크는 객체의 경계를 얻기 위해 에지정보를 사용하는데 실제 이미지에서 객체의 경계가 아닌 인접한 주위의 강한 애지(edge)에 대해서도 영향을 받게 되는 문제가 있다. 이러한 문제를 해결하기 위해 스테레오영상의 disparity 정보를 이용하여 이를 개선하고 disparity 측정에 사용되는 블록매칭(block matching)방법을 스네이크 알고리즘에 적용시켰다.