Segmentation and Recognition of Hand-drawn Situation Maps

Abstract

Abstract: Most of current research on online sketched military symbol recognition concerns the isolated samples. In pen-based situation marking systems, users prefer segmenting and recognizing the full sketched situation maps. However, it is a more difficult problem. The characteristics of hand-drawn situation maps and difficulties to segment them were analyzed, and a dynamic programming-based approach was proposed. A hand-drawn situation map was segmented coarsely by minimum spanning tree-based stroke clustering. The candidate segmentation path was evaluated by synthesizing geometric analysis and isolated symbol classifier together, using confidence transformation and fusion. The dynamic programming algorithm was used to search the optimal segmentation and recognition result. Experimental results demonstrate that the proposed method is effective, which extends the applications of sketch recognition.

Key words: sketch recognition, segmentation, situation maps, military symbols, dynamic programming

CLC Number:

TP391

Deng Wei, Wu Lingda, Zhang Yougen, Yang Chao. Segmentation and Recognition of Hand-drawn Situation Maps[J]. Journal of System Simulation, 2016, 28(8): 1884-1891.

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