Description of shape patterns using circular arcs for object detection

Cited 6 time in webofscience Cited 0 time in scopus
  • Hit : 375
  • Download : 0
The authors propose a novel object detection algorithm based on shape matching using a single sketch of an object. The proposed algorithm uses circular arc segments to describe image edges; this approach is advantageous for shape description, shape expression and reconstruction. Circular arcs are initially segmented from the image contour using the split-and-merge method, and they are extended, being partially overlapped with neighbouring circular arcs. The extracted circular arcs of the object sketch constitute an attributed relational graph as a structured object model. Circular arcs in the test image are refined by the bottom-up process of circular arc extension, and matched with circular arcs in the object model by the top-down process of end-point adjustment. The authors design end-point-based shape descriptors to encode local shape information. Hough voting aggregates the detection of circular arcs to localise the object. Probabilistic relaxation verifies the detection candidates and delineate the object boundaries. The proposed object detection system benefits from reliable extraction of contour segments, efficient and discriminative shape encoding, and flexible and robust shape matching. It exhibits competitive object detection performance in experiments using real images.
Publisher
INST ENGINEERING TECHNOLOGY-IET
Issue Date
2013-04
Language
English
Article Type
Article
Keywords

PROBABILISTIC RELAXATION; RECOGNITION; RETRIEVAL; HISTOGRAMS; SEGMENTS; FEATURES; MODEL

Citation

IET COMPUTER VISION, v.7, no.2, pp.90 - 104

ISSN
1751-9632
DOI
10.1049/iet-cvi.2011.0180
URI
http://hdl.handle.net/10203/175053
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 6 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0