Abstract

Today packaging waste is a prevalent issue due to the increase in deliveries from online shopping. Here a new approach to this issue of cardboard box packaging waste is proposed by adapting an image processing algorithm based on camera vision-based measurement that computes the optimal cuboid bounding algorithm of irregular shape products. The end result is utilized so that packaging workers select the appropriate product box. This approach may also be used as a preliminary process to optimize the packaging of many products into a single cardboard box. The system setup with two cameras is prepared to capture the overhead and sideview images, estimating the box’s width, depth, and height in pixels. This system may then evaluate feasible cuboids that minimize waste, in which the traditional Otsu’s thresholding method, proposed Otsu’s scheme, and 1-D gradient means are utilized to avoid inaccuracies created by shadows. Calibration is performed with a Rubik’s cube to convert the measurement from computer simulations to real-life dimensions. The computer simulations from the overhead and sideview images compared to the actual bounding box of the object show that the proposed algorithm yields superior performance by reducing the area error of the bounding box (%) of an overhead image and the height error (%) of a sideview image than the conventional Otsu’s method.

摘要

如今，由于网上购物送货量的增加，包装垃圾已成为一个普遍的问题。这里提出了一种解决纸板箱包装废物问题的新方法，通过采用基于相机视觉测量的图像处理算法来计算不规则形状产品的最佳长方体边界算法。利用最终结果，以便包装工人选择合适的产品包装盒。这种方法也可以用作优化将许多产品包装到单个纸板箱中的初步过程。配备两个摄像头的系统准备捕捉俯视和侧视图像，以像素为单位估计盒子的宽度、深度和高度。然后，该系统可以评估最小化浪费的可行长方体，其中传统的 Otsu 阈值方法、提出的 Otsu 方案、利用一维梯度方法来避免阴影造成的不准确。使用魔方进行校准，将计算机模拟的测量结果转换为现实生活中的尺寸。与物体的实际边界框相比，俯视图和侧视图像的计算机模拟表明，所提出的算法通过减少俯视图像的边界框的面积误差（％）和高度误差（％）而产生了优越的性能。与传统大津方法相比，侧视图像。