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다중 TMS320C31 DSP 를 사용한 3-D 비젼센서 Implementation
( Pierre Miche ),( Abdelaziz Bensrhair ),이상국 ( Sang Goog Lee ),( V.Oksenhendler ) 한국센서학회 1998 센서학회지 Vol.7 No.2
High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three ccomputational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a 64x32 bit instruction cache and two 1024x32 bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With 512x512 pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.
A High Speed Vision Algorithms for Axial Motion Sensor
Mousset, Stephane .,Miche, Pierre .,Bensrhair, Abdelaziz .,Lee, Sang Goog 한국센서학회 1998 센서학회지 Vol.7 No.6
In this paper, we present a robust and fast method that enables real-time computing of axial motion component of different points of a scene from a stereo images sequence. The aim of our method is to establish axial motion maps by computing a range of disparity maps. We propose a solution in two steps. In the first step we estimate motion with a low evel computing for an image point by a detection estimation-structure. In the second step, we use t,te neighbourhood information of the image point with morphology operation. The motion maps are established with a constant computation time without spatio-temporal matching.
CCD 카메라 얼굴 영상에서의 SVD 및 HMM 기법에 의한 눈 패턴 검출
진경찬 ( Kyung Chan Jin ),( Pierre MICHE ),박일용 ( Il Yong Park ),손병기 ( Byung Gi Sohn ),조진호 ( Jin Ho Cho ) 한국센서학회 1999 센서학회지 Vol.8 No.1
We proposed a method of eye pattern detection in the 2-D image which was obtained by CCD video camera. To detect face region and eye pattern, we proposed pattern search network and batch SVD algorithm which had the statistical equivalence of PCA. We also used HMM to improve the accuracy of detection. As a result, we acknowledged that the proposed algorithm was superior to PCA pattern detection algorithm in computational cost and accuracy of detection. Furthermore, we evaluated that the proposed algorithm was possible in real-time face pattern detection with 2 frame images per second.
P . 미셰,A . 벤스하이르,이상국 ( Pierre Miche,Abdelaziz Bensrhair,Sang Goog Lee ) 한국센서학회 1997 센서학회지 Vol.6 No.2
In this paper, we present an original stereo vision system which comprises two process: 1. An image segmentation algorithm based on new concept called declivity and using automatic thresholds. 2. A new stereo matching algorithm based on an optimal path search. This path is obtained by dynamic programming method which uses the threshold values calculated during the segmentation process. At present, a complete depth map of indoor scene only needs about 3 s on a Sun workstation IPX, and this time will be reduced to a few tenth of second on a specialised architecture based on several DSPs which is currently under consideration.