An Autoregressive Model Approach to Two-Dimensional Shape Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision, Graphics, and Image Processing
Inspection of 2-D objects using pattern matching method
Pattern Recognition
A fast parallel algorithm for thinning digital patterns
Communications of the ACM
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
On the Hough Technique for Curve Detection
IEEE Transactions on Computers
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
The Fibonacci search for cornerpoint detection of two-dimensional images
Mathematical and Computer Modelling: An International Journal
Pattern Recognition Letters
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In this paper, a string matching scheme is proposed to inspect two-dimensional objects for dimensional and shape verification in industrial environment. This approach consists of two stages. First, the procedures of determining the invariant starting point for boundary tracing and locating the cornerpoints of a curved object for polygon approximation are derived. To speed up the process, an optimization-based unconstrained line search method is used to locate the cornerpoints of the polygon image of a curved object. These cornerpoints are then recorded as feature string. At last, the feature string for each tested object are utilized to find the exact correspondence to one of several model objects. In contrast to conventional matching methods, which requires translation and rotation of the tested image before matching, the proposed method proves to be computationally efficient for real-time applications.