Research

year 2000 
author
Keyword Work Measurement, Motion Representation, Cycle Segmentation, 
Abstract Previous work measurement methods need much time and cost due to directly measuring time for work or are apt to include inaccuracy due to indirectly estimating it by using the previous reference data. In this study, we propose a method which efficiently measures time for work using digital image processing techniques. This method consists of two main steps: motion representation step and cycle segmentation step. In motion representation step, we first detect the motion of any object distinct from its background by subtracting between two consecutive images separated by a constant time interval and then, roughly locate the motion by using an edge detector and averaging coordinates of significant pixels of the edge image. Through these processes, the motion of the worker is represented by one dimensional time series data of worker location in horizontal and vertical axises. In cycle segmentation step, we extract the frames which have maximum or minimum coordinates in one cycle and store them

in a stack, and calculate each cycle time using these frames. In this step we also consider how to detect the event of camera area escape and work delay apt to happen in real work environments. To conclude, the experimental results show that the proposed method is useful for measuring time for work 
c MS 

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