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Information extraction of the moving objects based on edge detection and optical flow  

Chang, Min-Hyuk (조선대학교 전자${\cdot}$정보통신공학부 DSP&멀티미디어 연구실)
Park, Jong-An (조선대학교 전자${\cdot}$정보통신공학부 DSP&멀티미디어 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.27, no.8A, 2002 , pp. 822-828 More about this Journal
Abstract
Optical flow estimation based on multi constraint approaches is frequently used for recognition of moving objects. However, the use have been confined because of OF estimation time as well as error problem. This paper shows a new method form effectively extracting movement information using the multi-constraint base approaches with sobel edge detection. The moving objects anr extraced in the input image sequence using edge detection and segmentation. Edge detection and difference of the two input image sequence gives us the moving objects in the images. The process of thresholding removes the moving objects detected due to noise. After thresholding the real moving objects, we applied the Combinatorial Hough Transform (CHT) and voting accumulation to find the optimal constraint lines for optical flow estimation. The moving objects found in the two consecutive images by using edge detection and segmentation greatly reduces the time for comutation of CHT. The voting based CHT avoids the errors associated with least squares methods. Calculation of a large number of points along the constraint line is also avoided by using the transformed slope-intercept parameter domain. The simulation results show that the proposed method is very effective for extracting optical flow vectors and hence recognizing moving objects in the images.
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