Dimension Measurement and Key Point Detection of Boxes through Laser-Triangulation and Deep Learning-Based Techniques  
[PERSON]  
1 Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, 99 Shangda Road, Shanghai 200444, China; 17820125 [EMAIL_ADDRESS] (T.P. ); [EMAIL_ADDRESS] (Z.Z.) 1 Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, 99 Shangda Road, Shanghai 2004444, China; 17820125 [EMAIL_ADDRESS] (T.P. ); zjzhang@shu. laser light is the most widely used method and generate robust measurement results in practical industrial applications [9; 10; 11]. This technology has the characteristics of noncontact, wide range, high flexibility, fast speed, high precision, stable algorithms, simple structure, and good anti-interference. Moreover, the sensor is simple, economical, and easy to implement; thus, this technology has been widely used in many industrial fields, such as 3D shape measurement [12; 13], vision navigation [10], quality control [14; 15; 16; 17], and automatic inspection [18]. Some outstanding applications have used this technology in different fields. [PERSON] et al. [15] proposed a measurement and defect detection system for the weld bead on the line structured vision sensor, and the vision inspection system achieved satisfactory results for the online inspection. [PERSON] et al. [19] proposed a quality inspection system for steel rails based on a structured light measurement approach that intersects the rail through the structural light plane projected by the inner and the outer laser sensors. [PERSON] et al. [20] proposed a flatness detection apparatus based on multi-line structured light imaging, thereby achieving a detection accuracy of 99.74% for various computer keyboards in real production lines. Research on the dimension measurement of boxes in the field of computer vision technology has been published [3; 4; 5; 6; 7] and has achieved good results. In the present study, we used the line structured light vision to measure box dimensions. A novel 3D measurement scheme based on key points was developed, rather than directly applying complete 3D surface reconstruction. A portable, low-cost, and real-time dimension measurement system for the box based on a hand-held visual sensor was proposed, as shown in Figure 1a. Based on the laser triangulation and the detection of the adjacent face key points in the laser-box images, the system can compute the dimension parameters of the box with the 3D coordinates of these key points. The two main difficulties in the system are the detection of structural edges and the key points in the laser-box image and system calibration is another key part. However, most of these systems [14; 18; 19] should be operated in a fixed scenario to obtain excellent measurement results. When structured light sensors are used, robust light strip segmentation is the key step in detecting and precision positioning the structured edge of the laser-box image because it contains the local 3D information of the box dimension. However, we consider using the line laser vision device in a natural environment for box dimension measurement in this work. The laser light sources are disturbed by various noises, such as sunlight, shadows, and the appendages on the box surface, as shown in Figure 1b,c. Therefore, a robust algorithm is needed to accurately detect the structured edges and key point information in the image. The excellent performance of deep learning technology in image edge detection has made our study possible. Convolutional neural networks (CNN) are effective for edge detection tasks. [PERSON] et al.