基于扫描激光视觉传感的焊缝图像特征信息识别

特征点提取是激光视觉焊缝图像识别的关键技术,目前常用的斜率分析法虽然原理简单、计算速度快,但适应性不好、精度不高,对于一些复杂的深坡口焊缝甚至无法识别.对基于扫描激光视觉传感的焊缝图像识别进行深入研究后,提出一种新的特征点提取思想———由形到点,将焊缝坡口特征点分为直角拐点和斜角拐点,分别设计斜率极值法和斜率截距法来提取.实际焊缝跟踪时,根据拐点类型分别调用对应的提取算法,就能完成全部焊缝坡口所有特征点的提取.结果表明,"由形到点"提取特征点精度高,抗干扰能力强,对不同焊缝坡口形式适应性好,在厚板深坡口焊缝跟踪领域有很大的实用价值.

Features extraction for weld image of scanning laser sensing

Feature points extraction is the key to visual sensing and recognition of seam image. One of the most widelyused methods is to analyze slope of laser stripes,which is simple in principle and fast in computing speed. However,the method is indicated weak in adaptability and accuracy,even incapable for complex welding grooves. On the basis of exhaustive study on recognizing seam image from scanning-laser sensing system,a new idea called "feature from shaping" has been propounded that features points can be divided into inflection points at right angle and bevel angle based on the exact shape of seam groove. Both of two types of inflections are extracted by specially-designed algorithms,the former by method of extreme slope value and the latter by method of slope-intercept. During extraction in real-time seam tracking,corresponding algorithm is successively invoked according to the type of feature points until end of image processing. Experiments show that extracting feature points from shaping have advantages of high precision,strong anti-interference ability,good adaptability along with great practical value in the field of deep-groove seam tracking.