Transparent object recognition and retrieval for robotic bio-laboratory automation applications

This paper aims to develop a transparent object recognition algorithm which can integrate with visual cues of transparent objects to enhance the retrieval result. Due to the special characteristics of transparent objects, very few vision methods exist to identify them. To achieve our goal, we first use active depth sensor combining with image pre-processing techniques to retrieve transparent candidates. We then propose a transparent candidate classification algorithm using visual cues in color image to further distinguish the transparent ones out of candidates. Experimental results show that our algorithm can achieve good transparent object retrieval results and outperform methods based on depth image. In addition, this algorithm can be integrated with pose estimation methods on robotic bio-laboratory automation applications.