Robust Symbol Localization Based on Junction Features and Efficient Geometry Consistency Checking

This paper presents a new approach for symbol localization in line-drawing images using junction features and geometry consistency checking. The proposed system first detects junction points, and then characterizes them by very compact, distinctive, and varying-length descriptors. The detected junctions are used to decompose a document image into a set of smooth primitives composing of isolated shapes (e.g., isolated circles and straight lines) and curve segments bounded between either two junctions or a junction and an end-point. These primitives are then associated with a new set of key points to form a complete and compact representation of a graphical document. Next, key point matching is performed to find the correspondences among the key points of the query and those of database documents. The obtained matches are finally refined by a new and efficient algorithm to deal with the problem of geometry consistency checking. Our experiments showed that the proposed system is very time- and memory-efficient, and provides high accuracy rate of symbol localization.