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Automatic three-dimensional reconstruction based on four-view stereo vision using checkerboard pattern 被引量:5
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作者 XIONG Jie ZHONG Si-dong +1 位作者 LIU Yong tu li-fen 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第5期1063-1072,共10页
An automatic three-dimensional(3D) reconstruction method based on four-view stereo vision using checkerboard pattern is presented. Mismatches easily exist in traditional binocular stereo matching due to the repeatable... An automatic three-dimensional(3D) reconstruction method based on four-view stereo vision using checkerboard pattern is presented. Mismatches easily exist in traditional binocular stereo matching due to the repeatable or similar features of binocular images. In order to reduce the probability of mismatching and improve the measure precision, a four-camera measurement system which can add extra matching constraints and offer multiple measurements is applied in this work. Moreover, a series of different checkerboard patterns are projected onto the object to obtain dense feature points and remove mismatched points. Finally, the 3D model is generated by performing Delaunay triangulation and texture mapping on the point cloud obtained by four-view matching. This method was tested on the 3D reconstruction of a terracotta soldier sculpture and the Buddhas in the Mogao Grottoes. Their point clouds without mismatched points were obtained and less processing time was consumed in most cases relative to binocular matching. These good reconstructed models show the effectiveness of the method. 展开更多
关键词 three-dimensional reconstruction four-view STEREO VISION CHECKERBOARD pattern DENSE point
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基于图像传感器的钢板板坯喷标字符在线识别系统 被引量:4
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作者 彭祺 屠礼芬 +2 位作者 宋伟 唐戈锐 余振宇 《仪表技术与传感器》 CSCD 北大核心 2022年第12期57-61,共5页
针对钢板板坯生产过程中,待加热的钢板需要人工识别其喷标字符存在的危险系数高、效率低、容易产生视觉疲劳等问题,设计了一种基于图像传感器的钢板板坯喷标字符在线识别系统。该系统采用微视高感光工业相机HK-A5100-GM60-NIR采集图像,... 针对钢板板坯生产过程中,待加热的钢板需要人工识别其喷标字符存在的危险系数高、效率低、容易产生视觉疲劳等问题,设计了一种基于图像传感器的钢板板坯喷标字符在线识别系统。该系统采用微视高感光工业相机HK-A5100-GM60-NIR采集图像,其前端增加减光镜和滤光镜,以解决钢厂复杂的光照环境和图像传感器过饱和问题。并自制了相机温控防护系统,保证相机能在钢厂高温环境正常使用。软件方面,采用图像分析方法获取板坯字符区域,并使用Paddle-OCR字符识别算法对其进行识别。生产实践表明:该系统平均识别率为98.64%,图像采集和处理速率为33帧/s,字符识别算法平均用时0.2 s,达到在线识别要求。 展开更多
关键词 字符识别 钢板板坯 在线识别 高感光工业相机 Paddle-OCR
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