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Automatic Chinese Postal Address Block Location Using Proximity Descriptors and Cooperative Profit Random Forests.

Dong, X., Dong, J., Zhou, H., Sun, J. and Tao, D., 2017. Automatic Chinese Postal Address Block Location Using Proximity Descriptors and Cooperative Profit Random Forests. IEEE Transactions on Industrial Electronics, 65 (5), 4401-4412.

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DOI: 10.1109/TIE.2017.2764866

Abstract

Locating the destination address block is key to automated sorting of mails. Due to the characteristics of Chinese envelopes used in mainland China, we here exploit proximity cues in order to describe the investigated regions on envelopes. We propose two proximity descriptors encoding spatial distributions of the connected components obtained from the binary envelope images. To locate the destination address block, these descriptors are used together with cooperative profit random forests (CPRFs). Experimental results show that the proposed proximity descriptors are superior to two component descriptors, which only exploit the shape characteristics of the individual components, and the CPRF classifier produces higher recall values than seven state-of-the-art classifiers. These promising results are due to the fact that the proposed descriptors encode the proximity characteristics of the binary envelope images, and the CPRF classifier uses an effective tree node split approach.

Item Type:Article
ISSN:0278-0046
Uncontrolled Keywords:cooperative game theory; postal address block location; postal automation; proximity; random forests (RFs)
Group:Faculty of Media & Communication
ID Code:33297
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:31 Jan 2020 15:18
Last Modified:31 Jan 2020 15:18

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