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Proceedings Paper

Modification of YAPE keypoint detection algorithm for wide local contrast range images
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Paper Abstract

Keypoint detection is an important tool of image analysis, and among many contemporary keypoint detection algorithms YAPE is known for its computational performance, allowing its use in mobile and embedded systems. One of its shortcomings is high sensitivity to local contrast which leads to high detection density in high-contrast areas while missing detections in low-contrast ones. In this work we study the contrast sensitivity of YAPE and propose a modification which compensates for this property on images with wide local contrast range (Yet Another Contrast-Invariant Point Extractor, YACIPE). As a model example, we considered the traffic sign recognition problem, where some signs are well-lighted, whereas others are in shadows and thus have low contrast. We show that the number of traffic signs on the image of which has not been detected any keypoints is 40% less for the proposed modification compared to the original algorithm.

Paper Details

Date Published: 13 April 2018
PDF: 8 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 1069616 (13 April 2018); doi: 10.1117/12.2310243
Show Author Affiliations
A. Lukoyanov, Institute for Information Transmission Problems (Russian Federation)
Moscow Institute of Physics and Technology (State Univ.) (Russian Federation)
D. Nikolaev, Institute for Information Transmission Problems (Russian Federation)
I. Konovalenko, Institute for Information Transmission Problems (Russian Federation)


Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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