• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.227-232
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• 2010

This paper proposes the real time lip reading method in the embedded environment. The embedded environment has the limited sources to use compared to existing PC environment, so it is hard to drive the lip reading system with existing PC environment in the embedded environment in real time. To solve the problem, this paper suggests detection methods of lip region, feature extraction of lips, and awareness methods of phonetic words suitable to the embedded environment. First, it detects the face region by using face color information to find out the accurate lip region and then detects the exact lip region by finding the position of both eyes from the detected face region and using the geometric relations. To detect strong features of lighting variables by the changing surroundings, histogram matching, lip folding, and RASTA filter were applied, and the properties extracted by using the principal component analysis(PCA) were used for recognition. The result of the test has shown the processing speed between 1.15 and 2.35 sec. according to vocalizations in the embedded environment of CPU 806Mhz, RAM 128MB specifications and obtained 77% of recognition as 139 among 180 words were recognized.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.105-114
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• 2000

In this paper, we concentrate on an efficient method to decrease a lot of pixel data to be processed with an Image transform based automatic lipreading It is reported that the image transform based approach, which obtains a compressed representation of the speaker's mouth, results in superior lipreading performance than the lip contour based approach But this approach produces so many feature parameters of the lip that has much data and requires much computation time for recognition To reduce the data to be computed, we propose a simple method folding at the vertical center of the lip-image based on the symmetry of the lip In addition, the principal component analysis(PCA) is used for fast algorithm and HMM word recognition results are reported The proposed method reduces the number of the feature parameters at $22{\sim}47%$ and improves hidden Markov model(HMM)word recognition rates at $2{\sim}3%$, using the folded lip-image compared with the normal method using $16{\times}16$ lip-image.

• Journal of the Korean Society of Costume
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• v.35
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• pp.265-279
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• 1997

Through eight folding screens for Chac Rae and ban Cha Do we have learned the costumes of people who participate in Chac Rae ceremonty being accompanied by social positions. Firstly the costumes of crown prince can be classified in two parts. One is costumes of Chac Rae befor Kwan Rae the other is costumes of Chac Rae after Kwan Rae Also we know the costumes of Chac Rae before kwan Rae is consisted of SSangdonggae Gong-jungchak Chilchangbok Mean-while the crown prince wore Myunbok at chac rae after Kwan rae. Second Chakbongdo tell us various types of Youngbok by blue-black and red colored chulik Third we can see Uijangsu who wore Sangbok on Chakbongdo and know their brilliant costume colors on ban Cha Do through Hongmo on Chunguei Chungmo on honguei Hongmo on Honguei violet-Lip on honguei mean-while Kyokun wears Hongmo on Honguei and hoimo on Hoiuei. Forth regarding the costume of Byulgam Chakbongdo appears Chogun on Hongpo belting blue belt wearing blackboots Meantime ban Cha Do shows Chogun on Hongpo wearing shoes. As reviewed above we know various color and types of costumes through Chakbongdo & Ban Cha Do on Crown prince Chacraedogam and would lide to deepen Chac Rae of crown prince including the costumes of Chac Rae of the crown princess the eldest son of the crown price the eldest brother of the king.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.348-355
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• 2010

In spite of development in speech recognition technology, speech recognition under noisy environment is still a difficult task. To solve this problem, Researchers has been proposed different methods where they have been used visual information except audio information for visual speech recognition. However, visual information also has visual noises as well as the noises of audio information, and this visual noises cause degradation in visual speech recognition. Therefore, it is one the field of interest how to extract visual features parameter for enhancing visual speech recognition performance. In this paper, we propose a method for visual feature parameter extraction based on image-base approach for enhancing recognition performance of the HMM based visual speech recognizer. For experiments, we have constructed Audio-visual database which is consisted with 105 speackers and each speaker has uttered 62 words. We have applied histogram matching, lip folding, RASTA filtering, Liner Mask, DCT and PCA. The experimental results show that the recognition performance of our proposed method enhanced at about 21% than the baseline method.