Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

Sensors

Wan-Yu Chang²  Chung-Cheng Chiu¹  Jia-Horng Yang² 

[1] Department of Electrical and Electronic Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan County 33551, Taiwan;

关键词: connected components;    labeling algorithm;    decision tree;    scan mask;   

DOI  :  10.3390/s150923763

来源: mdpi

【 摘 要 】

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.