摘要
传统采用结构光视觉三维点云逐层三角网格化方法提取犯罪现场特征时,易受到噪声的干扰,导致特征提取准确率较低。提出基于智能激光视觉的犯罪现场特征提取方法,采用基于智能激光视觉检测方法检测犯罪现场指纹信息,规格化犯罪现场指纹图像,并获取指纹方向信息、指纹频率信息,对指纹图像进行滤波,通过向量点模式匹配算法提取滤波后的指纹图像的指纹特征。实验结果表明,所提方法可有效提取犯罪现场指纹特征,且对不同质量的指纹图像特征提取识别的平均准确率高达96. 98%,提取准确率较高;提取速度增长率高达30%,平均提取耗时约为110 s,特征提取效率较高。
The traditional method of triangulation of three-dimensional point cloud by layer of structure light vision is easy to be disturbed by noise,resulting in lower accuracy of feature extraction. This paper proposes a crime scene feature extraction method based on intelligent laser vision,adopts intelligent laser vision detection method to detect the fingerprint information at the crime scene,normalizes the fingerprint image at the crime scene,and obtains the fingerprint direction information and fingerprint frequency information,and filters the fingerprint image. Fingerprint characteristics of filtered fingerprint images are extracted by vector point pattern matching algorithm. The experimental results show that the proposed method can effectively extract the fingerprint characteristics of crime scene,and the average accuracy of different quality fingerprint image extraction and identification is as high as 96. 98%,and the accuracy of extraction is high. The extraction speed growth rate is as high as 30%,the average extraction time is about 110 s,and the feature extraction efficiency is higher.
引文
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