Search results

The purpose of this paper is to develop a robot vision system for surface defect detection of 3D objects. It aims at the ill‐defined qualitative items such as stains and scratches.

A robot vision system for surface defect detection may counter: high surface reflection at some viewing angles; and no reference markers in any sensed images for matching. A filtering process is used to separate the illumination and reflection components of an image. An automatic marker‐selection process and a template‐matching method are then proposed for image registration and anomaly detection in reflection‐free images.

Tests were performed on a variety of hand‐held electronic devices such as cellular phones. Experimental results show that the proposed system can reliably avoid reflection surfaces and effectively identify small local defects on the surfaces in different viewing angles.

The results have practical implications for industrial objects with arbitrary surfaces.

Traditional visual inspection systems mainly work for two‐dimensional planar surfaces such as printed circuit boards and wafers. The proposed system can find the viewing angles with minimum surface reflection and detect small local defects under image misalignment for three‐dimensional objects.

This study aims to propose a door detection method based on the door properties in both depth and gray-level images. It can further help blind people (or mobile robots) find the doorway to their destination.

The proposed method uses the hierarchical point–line region principle with majority vote to encode the surface features pixel by pixel, and then dominant scene entities line by line, and finally the prioritized scene entities in the center, left and right of the observed scene.

This approach is very robust for noise and random misclassification in pixel, line and region levels and provides sufficient information for the pathway in the front and on the left and right of a scene. The proposed robot vision-assist system can be worn by visually impaired people or mounted on mobile robots. It provides more complete information about the surrounding environment to guide safely and effectively the user to the destination.

In this study, the proposed robot vision scheme provides detailed configurations of the environment encountered in daily life, including stairs (up and down), curbs/steps (up and down), obstacles, overheads, potholes/gutters, hazards and accessible ground. All these scene entities detected in the environment provide the blind people (or mobile robots) more complete information for better decision-making of their own. This paper also proposes, especially, a door detection method based on the door’s features in both depth and gray-level images. It can further help blind people find the doorway to their destination in an unfamiliar environment.