| Project/Area Number |
12044202
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas
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| Allocation Type | Single-year Grants |
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| Review Section |
Science and Engineering
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| Research Institution | TOHOKU UNIVERSITY |
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Principal Investigator |
OHMI Tadahiro New Industry Creation Hatchery Center, Professor, 未来科学技術共同研究センター, 教授 (20016463)
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| Co-Investigator(Kenkyū-buntansha) |
HIRAYAMA Masaki New Industry Creation Hatchery Center, Associate Professor, 未来科学技術共同研究センター, 助教授 (70250701)
KOTANI Koji Graduate School of Engineering, Associate Professor, 大学院・工学研究科, 助教授 (20250699)
TSUBOUCHI Kazuo Research Institute of Electrical Communication, Professor, 電気通信研究所, 教授 (30006283)
MIURA Michiko Hiroshima University, Professor, 大学院・先端物質科学研究科, 教授 (70291482)
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| Project Period (FY) |
2000 – 2002
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| Keywords | Vector Quantization / Codebook Spectrum / Image Compression / Face Recognition / Real-Time Processing / LSI Design |
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| Research Abstract |
In order to realize real-time efficient image compression, we have developed the adaptive resolution vector quantization technique (AR-VQ). The adaptive resolution conversion method changes the resolution of image adaptively according to the form of a pixel block texture. The AR-VQ has realized a much superior compression performance difference of 5 to 40 dB in compressed image quality than the worldwide standard the JPEG and the JPEG2000 for the images including text. We have also developed an advanced VQ encoding method and have implemented it into hardware architecture. The processor employs the needless calculation elimination method and the AR-VQ technique. An evaluation board has been developed in order to verify the performance of still-image encoding system employing the processor. The AR-VQ algorithm and wireless network technology make it possible to produce a wireless LAN data projector, in 2002.
In addition, we have developed a very simple yet highly reliable face recognition method based on the VQ histogram method in order to resolve real-time image recognition. The adjacent pixel intensity difference quantization histogram method has realized human face recognition at video-rate. Experimental results show a recognition time for 400 images of 40 persons (10 images per person) within 31msec, maintaining a recognition rate of 95.7% equal to the VQ histogram method.
Furthermore, we have developed an extracting methodology of variability in order to realize a high-reliability LSI design. The method can measure inter-chip variability and intra-chip variability each other.
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