High Points Recognition Method of Scraped Surface Based on Background Subtraction
Using computer vision library OpenCV, a method of automatic recognition high points of scraped workpiece surface is presented. The image is dealt with by background subtraction, Median filtering, morphological processing, image negates, contour finding and drawing contours. In order to accurately and efficiently recognize the high-point contours and mark its center positions, mathematical morphology and specific processing function were used.
Research and application of edge detection operator based on mathematical morphology
In order to extract image edge information and eliminate noise,according to enlightenment of three indexes to evaluate the merit and inferior of edge detection by Canny and thinking of multiple structuring elements,two improvements are made to the general mathematic morphology edge detection:first,the image is filtered using compound mathematic morphology filter;second,the mathematic morphology edge detection operator with multiple structuring elements and noise elimination is constructed using multiple structuring elements thinking.The steps using this improved mathematic morphology edge detection algorithm are summarized.The experimental result indicates that this method can retain more edge information and resolve the conflict between Signal-to-Noise and single edge response to some extent.Finally,this method is used in the leakage test and a new leakage test method is obtained.
Digitalization and Intellectualization of Scraping Operation (1st Report) -Investigation of a Series of Scraping Operation by Skilful Worker-
An automated scraping system with a machine tool and an image processing system has been developed in previous studies. In order to use the system as a highly precise and efficient system, it is necessary to intellectualize the scraping system like a skilful worker. This paper describes an investigation (digitalization) of a scraping operation by a skilful worker so that future studies can achieve effective and intelligent scraping system by means of the digitalized operation. In each step of the scraping operation, an image of the scraped workpiece with black bearing was obtained by a digital camera with a contrivance of imaging method and the information of the black bearing was obtained by image processing from the image. Moreover, a 3-D shape data of the workpiece was measured by a laser displacement meter on a machine tool. In the evaluation of the scraping operation, a height histogram of a 3-D shape data is useful. As a result, a strategy for smart and intelligent scraping was guessed from the investigation.