摘要
针对刀具柱面Data Matrix码图像拼接的特殊需求,已有算法拼接结果识读率低、实时性差的缺陷,提出了一种基于Data Matrix码图像特征的拼接方法.该方法基于缝隙内旋转采集的刀具柱面Data Matrix码序列图像,通过条码纵向位移校正与模块划分,完成基于模块信息的最小欧氏距离图像粗配准和归一化互相关图像精配准;为了保证条码结构正确,消除无重合区域对图像拼接的影响,根据匹配度先将序列图像融合成3部分并校正畸变;最后将这3部分按条码模块关系融合成一幅尺寸正确的图像,实现了条码定位、模块划分,以方便后续进行解码.实验结果表明,文中方法能够满足刀具柱面Data Matrix码序列图像的拼接需求,拼接结果解码正确率达到96%,拼接时间小于250ms,并且大大提高了解码速度.
In the light of the special requirement of image mosaic of Data Matrix barcode which marked on cylindrical surface of tool, a new mosaic method is presented based on the feature of Data Matrix barcode image to remedy the shortages of current image mosaic algorithms. In our method, an image collection device with a gap is used to gather the sequence bareode images by rotating the tool which is put in the gap, then these images are corrected to eliminate the longitudinal displacement and divided into barcode modules, after that the algorithms based on minimum Euclidean distance and normalized cross-correlation are used to achieve images registration. In order to keep the bareode structure right and to avoid the failure caused by non-overlap images, these sequence images are fused into three parts at first according to the matching degree, then these three parts are corrected to eliminate the distortion and finally fused into a right size image according to modules. Our method can obtain the barcode position and the module division at the same time. The decoding rate of the method achieves 96% and the mosaic time is less than 250 ms in experiment
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2013年第5期631-638,645,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(51275419)
国防基础预研项目
西北工业大学研究生创业种子基金资助(Z2012035)