Gabor Filtering-Based Scale and Rotation Invariance feature for 2D Barcode Region Detection

摘要：

2D barcode region detection is a non trivial problem for barcode revognition and decoding especially in complex backgrounds. Currently, morphological processing has been widely applied to extract potential regions of Data Matrix barcodes due to its low computation complexity. However, this method leads to two problems, adaptive selection of morphological structuring element and high false accept rate. To solve these problems, this paper proposes an innovative method for 2D barcode region detection based on Gabor filtering and BP neural network. The contributions are two folds: I) we propose a texture feature formulation independent of scale and rotation; 2) BP neural network can avoid the difficulty in morphological structure construction. Large scale experiments show the accuracy and robustness of the proposed method over the traditional morphological method.

关键词： 2D barcode gabor filtering teaxture feature neural network

作者: Meng Wang Li-Na Li Zhao-Xuan Yang

作者单位: School of Electronic Information Engineering Tianjin University Tianjin, China 300072

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 34-37

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）