Shape based recognition using freeman chain code and modified Needleman-Wunsch
Ema Rachmawati, Masayu Leylia Khodra, Iping Supriana · 2016
Contours are one of the most commonly used shape descriptors in object recognition problem. In this paper, we proposed object recognition system based on shape. The shape is obtained by extracting the contour of the object in the image using common techniques in image processing domain. Further, the shape is represented by using chain coding technique and the chain coded representation is modified into the set of segments, with each segment has a particular weight in accordance with its length in its polygonal approximation of the object shape. For the purpose of similarity calculation, we modified a common algorithm used in Bioinformatics field, namely Needleman-Wunsch algorithm, in the term of scoring function. We created a new definition and implementation of the substitution matrix (for the purpose of scoring function), according to the characteristics of set of line segment. From the experiment we have conducted, we successfully shown that the weight of each segment of the object shape has positive impact in the similarity calculation, shown by the precision and recall value.