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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yagi, Masakazu Shibata, Tadashi |
| Copyright Year | 2002 |
| Description | Author affiliation: Department of Electronics Engineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656 Japan (Yagi, Masakazu) || Department of Frontier Informatics, School of Frontier Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656 Japan (Shibata, Tadashi) |
| Abstract | A human-like robust image recognition system inspired by a psychological brain model [1] has been developed aiming at direct implementation in the VLSI hardware. The Principal Axis Projection (PAP) technique [2] has been employed for feature vector generation, which very well represents the human-perception of similarity in images while substantially reducing the dimensionality. In this study, we have introduced the concept of multi resolution and PAP kernel scanning in the PAP based vector matching algorithm. As a result, very robust image recognition has been demonstrated in gray scale images as well as in binary images. Interestingly, a large digit pattern formed as an aggregation of miniature digits like that shown in Fig. 1 can also be successfully recognized not only in the constituent small digits but also in the entire feature. Although the present algorithm is computationally very expensive, it has been designed fully compatible to execution on VLSI chips which we have developed for vector matching [3–5] and PAP vector generation. |
| File Size | 1951847 |
| File Format | |
| ISBN | 0780374029 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2002.5743974 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-05-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Kernel Image resolution Algorithm design and analysis Logic gates Psychology Integrated circuits Hardware |
| Content Type | Text |
| Resource Type | Article |
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