Object Recognition Through the Principal Component Analysis of Spatial Relationship Amongst Lines

This paper introduces a novel scheme which works on symbolizing every line in an object image for object recognition. Symbolizing is accomplished in terms of angles of intersection with regard to a line under consideration. Spatial relationship existing among the symbolized lines is represented using the notion of Triangular Spatial Relationship (TSR). A set of quadruples which preserves the TSR is subjected to principal component analysis to obtain the principal component vectors. These vectors are then stored in the knowledgebase for the purpose of recognition. Experimental results demonstrate that the proposed approach is efficient, invariant to linear transformations and capable of learning. To substantiate the success of the proposed model, a comparative study is performed with Murase and Nayar