Contour segmentation and invariant coding in view of automatic assembly
Georges Karavias, Georges Stamon, Almanto Scrizzi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Our problem is to find an efficient pattern-matching method in two dimensions in order to solve a puzzle automatically. The contours of the objects must first be coded in order to be analyzed. A contour descriptor code that is quite invariant to rotation, translation, and scaling of the original object is proposed. It is an extension of the Freeman and Shape Descriptor codes. The code is based on approximating the contour by linear segments and arcs. A robust segmentation method to cut up the contour in pieces well adapted to the approximation is needed. Such a method is proposed here, namely one that segments a puzzle piece in four sides using a Hough-transform based algorithm. The roughly linear segments forming each side are detected by the transform in order to detect the frontiers of each side. Each contour piece is then encoded using the before mentioned code. The resulting database of all the piece's side codes will be used in combination with morphological features, extracted from the contour codes using morphological operators, to detect pieces sharing a common side and assemble them automatically.