Volume 10, Number 6

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

  Authors

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

  Abstract

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.

  Keywords

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