• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.3 s.118
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• pp.248-256
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• 2007

In this paper, we propose a selective DFT spreading method to solve a high PAPR problem in uplink OFDMA system. A selective characteristic is added to the DFT spreading, so the DFT spreading method is mixed with SLM method. However, to minimize increment of computational complexity, differently with common SLM method, our proposed method uses only one DFT spreading block. After DFT, several copy branches are generated by multiplying with each different matrix. This matrix is obtained by linear transforming the each phase rotation in front of DFT block. And it has very lower computational complexity than one DFT process. For simulation, we suppose that the 512 point IFFT is used, the number of effective sub-carrier is 300, the number of allowed sub-carrier to each user's is 1/4 and 1/3 and QPSK modulation is used. From the simulation result, when the number of copy branch is 4, our proposed method has more than about 5.2 dB PAPR reduction effect. It is about 1.8 dB better than common DFT spreading method and 0.95 dB better than common SLM which uses 32 copy branches. And also, when the number of copy branch is 2, it is better than SLM using 32 copy branches. From the comparison, the proposed method has 91.79 % lower complexity than SLM using 32 copy branches in similar PAPR reduction performance. So, we can find a very good performance of our proposed method. Also, we can expect the similar performance when all number of sub-carrier is allocated to one user like the OFDM.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.431-438
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• 2020

In this paper, the method to extract lip contour by multiple threshold is proposed. Spyridonos et. el. proposed a method to extract lip contour. First step is get Q image from transform of RGB into YIQ. Second step is to find lip corner points by change point detection and split Q image into upper and lower part by corner points. The candidate lip contour can be obtained by apply threshold to Q image. From the candidate contour, feature variance is calculated and the contour with maximum variance is adopted as final contour. The feature variance 'D' is based on the absolute difference near the contour points. The conventional method has 3 problems. The first one is related to lip corner point. Calculation of variance depends on much skin pixels and therefore the accuracy decreases and have effect on the split for Q image. Second, there is no analysis for color systems except YIQ. YIQ is a good however, other color systems such as HVS, CIELUV, YCrCb would be considered. Final problem is related to selection of optimal contour. In selection process, they used maximum of average feature variance for the pixels near the contour points. The maximum of variance causes reduction of extracted contour compared to ground contours. To solve the first problem, the proposed method excludes some of skin pixels and got 30% performance increase. For the second problem, HSV, CIELUV, YCrCb coordinate systems are tested and found there is no relation between the conventional method and dependency to color systems. For the final problem, maximum of total sum for the feature variance is adopted rather than the maximum of average feature variance and got 46% performance increase. By combine all the solutions, the proposed method gives 2 times in accuracy and stability than conventional method.