A Guide on Getting High-Resolution 3D Color Point Cloud!

Abstract 

This application note explores the use of combining Basler color 2D camera and Photoneo 3D scanner to create a high-resolution color point cloud for applications such as shipping container inspections. 

Problem Statement

Did you know that shipping containers go through a meticulous inspection process? The quality of the shipping containers often decides which type of products should go into them. For example, newer and unused containers would contain food products, while used containers are graded from cargo-worthy to as-is. 

If used frequently, the outer surface of the containers would sometimes go through wear and tear, and would often sustain damages. Most users would do quality checks on these containers for dents and cracks, and would often need a high-resolution image for further quality checks and labelling inspections. While visible to the human eye, measuring the depth of the dents and cracks by hand would be quite tedious. Usually, a 3D scanner would be sufficient to capture and measure the depth of the dents and cracks. However, the point cloud produced would not be of high-resolution, and labels on the shipping containers would not appear. 

Thus, how do we go about this problem? 

Solution

Figure 1: Setup Image with Basler ace color camera acA5472-17uc, Photoneo Phoxi 3D Scanner L and a container.

For this application, the Soda Vision Tech Team used both a Basler ace color camera acA5472-17uc and a Photoneo Phoxi 3D Scanner L.

Figure 2: 2D color image capture, taken with Basler acA5472-17uc camera.

The Basler ace color camera produces high-resolution 2D images of the shipping containers for quality checks. In contrast, the Photoneo Phoxi 3D scanner produces a 3D point cloud which users can use to measure the depth of the dents and cracks. On its own, the 2D color camera is unable to produce a depth image where users can identify and measure the severity of the damage. When the Basler camera is combined with the 3D scanner, users are able to see the depth of the damage, as well as a high-resolution color image, creating a high-resolution 3D color point cloud.

Figure 3: 3D point cloud using Photoneo Phoxi 3D Scanner L

Figure 4: 3D color point cloud using Basler acA5472-17uc camera and Photoneo Phoxi 3D Scanner L

In order for the 3D color point cloud to be produced, Photoneo provides an API (Application Programming Interface), known as Phoxi API, for the calibration and transformation of both 2D color image and 3D point cloud. The Phoxi API is able to calibrate between the 2D and 3D parameters, which helps to match the image coordinates so that both 2D and 3D components will be synced. After the calibration process, a 3D high-resolution point cloud and a 2D high-resolution image are used, producing a high-resolution color 3D point cloud.

Figure 5: Diagram of the working principle of Photoneo Phoxi API

With the Photoneo Phoxi API, users only need to calibrate the 2D and 3D parameters once. From there, they can produce any 3D color point cloud for any object without further calibration. Moreover, the interface is able to integrate into C++ and C# programming. 

Users can use this application setup for Food Inspections and Robot Visions.

 

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