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Feature Point Detection by Combining Advantages of Intensity-based Approach and Edge-based Approach

Title
Feature Point Detection by Combining Advantages of Intensity-based Approach and Edge-based Approach
Author(s)
Kim, SunghoPark, ChaehoonChoi, YukyungKwon, SoonKweon, In So
DGIST Authors
Kim, SunghoPark, ChaehoonChoi, YukyungKwon, SoonKweon, In So
Issued Date
2012
Type
Article
ISSN
2010-376X
Abstract
n this paper, a novel corner detection method is presented to stably extract geometrically important corners. Intensity-based corner detectors such as the Harris corner can detect corners in noisy environments but has inaccurate corner position and misses the corners of obtuse angles. Edge-based corner detectors such as Curvature Scale Space can detect structural corners but show unstable corner detection due to incomplete edge detection in noisy environments. The proposed image-based direct curvature estimation can overcome limitations in both inaccurate structural corner detection of the Harris corner detector (intensity-based) and the unstable corner detection of Curvature Scale Space caused by incomplete edge detection. Various experimental results validate the robustness of the proposed method. Keywords—Feature, intensity, contour, hybrid.
URI
http://hdl.handle.net/20.500.11750/13410

https://pdfs.semanticscholar.org/1b50/6fa82f45d6bc5dce302cd4def7e0d0340638.pdf?_ga=2.130762445.356568445.1523849608-1083682479.1519189717
Publisher
International Journal of Computer, Electrical, Automation, Control and Information Engineering
Related Researcher
  • 권순 Kwon, Soon
  • Research Interests computer vision; deep learning; autonomous driving; parallel processing; vision system on chip
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Appears in Collections:
Division of Automotive Technology 1. Journal Articles

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