Sensitivity analysis for object recognition from large structural libraries

The paper studies the structural sensitivity of line pattern recognition using shape graphs. We compare the recognition performance for four different algorithms. Each algorithm uses a set of pairwise geometric attributes and a neighbourhood graph to represent the structure of the line patterns. The first algorithm uses a pairwise geometric histogram, the second uses a relational histogram on the edges of the shape graph, the third compares the set of attributes on the edges of the shape graph and the final algorithm compares the arrangement of line correspondences using graph matching. The different algorithms are compared under line deletion, line addition, line fragmentation and line end point measurement errors. It is the graph matching algorithm which proves to be the most effective.