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초록
영어
In this paper we present a novel container ISO-code recognition method which uses vertical edge information, a spatial structure window, and texture clustering. The vertical edge information is extracted using a top-hat transform. The candidate region and type of ISO-Code is obtained using a Spatial Structure Window (SSW) which wraps around the vertical edges. The ISO-Code is extracted using texture clustering by the K-Means algorithm which is then recognized by a Back-propagation Neural Network (BP). Experiments confirmed the robustness of the recognition algorithm on real images and videos.
목차
Abstract
1. Introduction
2. The System Overview
3. Extracting the container ISO-code
3.1. The Top-hap Morphology
3.2. The Character Mask
3.3. The Spatial Structure Window
4. Character Extraction
4.1. Binarization
4.2. K-Means Clustering
5. Character Recognition
6. Experiments
7. Conclusion
References
1. Introduction
2. The System Overview
3. Extracting the container ISO-code
3.1. The Top-hap Morphology
3.2. The Character Mask
3.3. The Spatial Structure Window
4. Character Extraction
4.1. Binarization
4.2. K-Means Clustering
5. Character Recognition
6. Experiments
7. Conclusion
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보