A FAST AUTOMATED VISION SYSTEM FOR CONTAINER CORNER CASTING RECOGNITION

Authors

Chao Mi, Container Supply Chain Tech. Engineering Research Center, Shanghai Maritime University, No.1550 Haigang Ave, Shanghai 201306, PR ChinaFollow
Zhiwei Zhang, Logistics Engineering College, Shanghai Maritime University, No.1550 Haigang Ave, Shanghai 201306, PR China.
Youfang Huang, Container Supply Chain Tech. Engineering Research Center, Shanghai Maritime University, No.1550 Haigang Ave, Shanghai 201306, PR China
Yang Shen, Higher Technical College, Shanghai Maritime University, Shanghai, 201306, PR China.

Abstract

With the development of container port automation, the automated vision systems for containers have been widely used in automated ports. This paper presents a rapid automated vision system for container corner casting recognition. The histograms of oriented gradients (HOG) descriptors are used to preprocess the image of the container and the vectors of HOG are then built. A trained support vector machine (SVM) classifier is applied to recognize the right corner casting of the container. At last, through symmetry, a flipping mirror algorithm is used for quick left corner casting recognition. The experimental results show this algorithm scans and detect the two corner castings of the container almost twice as fast as the traditional algorithms.

Recommended Citation

Mi, Chao; Zhang, Zhiwei; Huang, Youfang; and Shen, Yang (2016) "A FAST AUTOMATED VISION SYSTEM FOR CONTAINER CORNER CASTING RECOGNITION," Journal of Marine Science and Technology: Vol. 24: Iss. 1, Article 8.
DOI: 10.6119/JMST-016-0125-8
Available at: https://jmstt.ntou.edu.tw/journal/vol24/iss1/8