CNC Laser Cutting Machine Automatic Camera Contour Positioning Algorithm

The CNC laser automatic cutting machine in engineering has a very important application value. CNC laser cutting machine automatic camera contour positioning algorithm is a part of CNC laser cutting technology core algorithm. Implementing this algorithm we can get the vector coordinate information, by making the vector coordinate information into the control chip then be achieved automatically cutting the workpiece in engineering. The weakness of traditional seeking the edge algorithms like Roberts operator, Sobel operator in practical engineering applications are slow in process and poor in anti-noise capability. The wavelet and it's multi-scale analysis theory can solve these problems well and be able to portray a good image gray-scale changes.In this thesis, we studied the theory of automatic camera positioning algorithm and implementation. The mainly work are done in the following areas:(1) We utilizes antisymmetric dyadic wavelet to extract the edges information of workpiece product in the image. In the edge extraction process, some of the weak edge is very difficult to detected, so we need to use the two-level threshold to make edge connection.(2) Then thinning and outer contour tracing to the connected edge, thinning using zhang-sun Parallel algorithm, this algorithm through two iterative algorithm can thin edge to single-pixel point,also cannot destroy the connectivity of the original edge image.The outer contour tracing using eighthborhood tracing algorithm,the algorithm is computationally fast and accurate location tracking, all these are prepared for the edge vector processing.(3) We vector the edge that we have pretreatmented, firstly encoded the edge of the pretreatment use Freeman chain code, then based on the linear fitting algorithm to achieve the edge vector.Since the algorithm used in C language, so it makes the edge location accuracy, processing speed, and meeting the engineering requirements. Not excessive considered program robustness is the deficiencies in this program, hoping the research can be solved and improved in the next step.