Volume 10, Number 6

2D Features-based Detector and Descriptor Selection System for Hierarchical Recognition of Industrial Parts


Ibon Merino1, Jon Azpiazu1, Anthony Remazeilles1 and Basilio Sierra2, 1Tecnalia Research and Innovation, Spain and 2University of the Basque Country UPV/EHU, Spain


Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method like ORB, SIFT or FREAK, despite being fairly slower.


Computer vision, Descriptors, Feature-based object recognition, Expert system