A new method for expiration code detection and recognition using gabor features based collaborative representation |
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| Affiliation: | 1. University of Tunis, Tunis National Higher School of Engineering (ENSIT), Laboratory of Signal Image and Energy Mastery (SIME), 5 Avenue Taha Hussein, 1008 Tunis, Tunisia;2. Jordan University of Science and Technology, Irbid 22110, Jordan;3. School of Electronics and Information Engineering, Sichuan University, Chengdu 610064, China;1. HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong;2. College of Information Engineering, Shenzhen University, China;3. Guangdong Polytechnic Normal University, Guangzhou, China;4. Huaiji Dengyun Auto-parts (Holding) Co., Ltd., Huaiji, Zhaoqing, Guangdong, China;5. Institute of Intelligent Computing Science, Shenzhen University Shenzhen, China;1. Department of Civil and Environmental Engineering, Carnegie Mellon University, 119 Porter Hall, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States;2. Polytechnic School of Engineering, New York University, 6 MetroTech Center, Brooklyn, NY 11201, United States;3. College of Engineering, Carnegie Mellon University, 110 Scaife Hall, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States;1. The University of Electro-Communications, Japan;2. The University of Tokyo, Japan;1. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N Mathews Ave., Urbana, IL 61801, United States;2. Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N Goodwin Ave., Urbana, IL 61801, United States;3. Department of Civil and Environmental Engineering and Department of Computer Science, University of Illinois at Urbana-Champaign, 205 N Mathews Ave., Urbana, IL 61801, United States |
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| Abstract: | Text in images and video contains important information for visual content understanding, indexing, and recognizing. Extraction of this information involves preprocessing, localization and extraction of the text from a given image. In this paper, we propose a novel expiration code detection and recognition algorithm by using Gabor features and collaborative representation based classification. The proposed system consists of four steps: expiration code location, character isolation, Gabor features extraction and characters recognition. For expiration code detection, the Gabor energy (GE) and the maximum energy difference (MED) are extracted. The performance of the recognition algorithm is tested over three Gabor features: GE, magnitude response (MR) and imaginary response (IR). The Gabor features are classified based on collaborative representation based classifier (GCRC). To encompass all frequencies and orientations, downsampling and principal component analysis (PCA) are applied in order to reduce the features space dimensionality. The effectiveness of the proposed localization algorithm is highlighted and compared with other existing methods. Extensive testing shows that the suggested detection scheme outperforms existing methods in terms of detection rate for large image database. Also, GCRC show very competitive results compared with Gabor feature sparse representation based classification (GSRC). Also, the proposed system outperforms the nearest neighbor (NN) classifier and the collaborative representation based classification (CRC). |
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| Keywords: | Text detection Optical character recognition Gabor features Sparse representation Collaborative representation Principal component analysis |
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