Next Article in Journal
Classification of Normal and Abnormal Regimes in Financial Markets
Previous Article in Journal
Special Issue on Algorithms for the Resource Management of Large Scale Infrastructures
Article Menu

Export Article

Open AccessArticle
Algorithms 2018, 11(12), 201; https://doi.org/10.3390/a11120201

A Fast Approach to Texture-Less Object Detection Based on Orientation Compressing Map and Discriminative Regional Weight

Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
*
Author to whom correspondence should be addressed.
Received: 24 October 2018 / Revised: 4 December 2018 / Accepted: 6 December 2018 / Published: 12 December 2018
Full-Text   |   PDF [4761 KB, uploaded 12 December 2018]   |  

Abstract

This paper presents a fast algorithm for texture-less object recognition, which is designed to be robust to cluttered backgrounds and small transformations. At its core, the proposed method demonstrates a two-stage template-based procedure using an orientation compressing map and discriminative regional weight (OCM-DRW) to effectively detect texture-less objects. In the first stage, the proposed method quantizes and compresses all the orientations in a neighborhood to obtain the orientation compressing map which then is used to generate a set of possible object locations. To recognize the object in these possible object locations, the second stage computes the similarity of each possible object location with the learned template by using discriminative regional weight, which can effectively distinguish different categories of objects with similar parts. Experiments on publiclyavailable, texture-less object datasets indicate that apart from yielding efficient computational performance, the proposed method also attained remarkable recognition rates surpassing recent state-of-the-art texture-less object detectors in the presence of high-clutter, occlusion and scale-rotation changes. It improves the accuracy and speed by 8% and 370% respectively, relative to the previous best result on D-Textureless dataset. View Full-Text
Keywords: texture-less object; object detection; template matching; possible object locations; orientation compressed map; real-time detection texture-less object; object detection; template matching; possible object locations; orientation compressed map; real-time detection
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Yu, H.; Qin, H.; Peng, M. A Fast Approach to Texture-Less Object Detection Based on Orientation Compressing Map and Discriminative Regional Weight. Algorithms 2018, 11, 201.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top