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高噪声环境下的快递包裹条形码的快速定位分割识别 被引量:3

Fast Positioning and Segmentation Identification of Express Parcel Bar Codes in High Noise Environment
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摘要 随着国内物流行业的快速发展,人们对于快递包裹派送信息的快速查询的需求日益迫切,快递单号的自动化获取有望解决该问题。该文针对复杂环境下的包裹单扫描件图像中的条形码/二维码定位分割识别问题,提出了一套条形码区域定位分割识别算法,将原始图像从RGB空间转换成HSV空间,之后使用MSRCR算法进行增强处理。整个算法在实际快递单扫描件图像中进行了充分测试,结果显示本算法快速、准确、误码率低,具有很强的实用价值。 With the rapid development of the domestic logistics industry, the demand for quick inquiry of express parcel delivery information is becoming more and more urgent, and the automatic acquisition of express delivery number is expected to solve this problem.This paper proposes a bar code region location segmentation recognition algorithm for bar code/QR code location segmentation recognition in a single scan image of a parcel in a complex environment.The original image is converted from RGB space to HSV space, and then MSRCR algorithm is used. Enhance processing.The whole algorithm is fully tested in the actual express single scan image.The results show that the algorithm is fast, accurate and has low bit error rate, and has strong practical value.
作者 王宁 姜全春 蒋林华 WANG Ning;JIANG Quan-chun;JIANG Lin-Hua(Shanghai university of technology,School of optoelectronic information and computer engineering,Shanghai,200082,China)
出处 《软件》 2019年第7期80-83,共4页 Software
基金 国家自然科学基金(No.61775139)
关键词 快递扫描件 MSRCR HSV色彩空间 Scanned express form MSRCR HSV color space
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