Light strip extraction is important in a structured light measurement system. However, the extraction of light strip is incomplete, losing the information, in the detection of highly reflective surface. This paper presents an iterative threshold segmentation algorithm based on information entropy. Firstly, the image is initially segmented, then using the eightneighborhood detection to remove the noise and retain the light strip, after which the iterative segmentation is carried out with the inflection point of the information entropy of the extracted image as the termination condition to improve the integrity of the light strip segmentation and avoid the excessive segmentation of the background. Compared with the results of Otsu algorithm, the proposed method can retain more complete light strip information, with fewer breaking points.
Line-structured light sensor is a three-dimensional measurement method which combines the advantage of high precision and speed, applicable in many fields. The mathematical model of line-structured light sensor is an essential foundation which determines measurement precision. Through the comparison of the three representative models which are deduced from different starting points and analysis of the model constraint conditions, we build a uniform and flexible model which shows the common characteristics and connections of the previous models and combines the flexibility and clear geometric meanings of the structured parameters with a correctable constraint condition. It is suitable to most conditions and structured parameters design of line-structured light sensor.
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