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L-shaped geometry-based pattern descriptor serving shape retrieval
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AI
DOI：10.1016/j.eswa.2022.119260.png)
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摘要
En 中文
Feature representation patterns serving shape retrieval have gained considerable attention over recent years. Accordingly, a geometry-based characterization arrangement based on the L-shape pattern is adopted in this paper for shape description. The presented L-shape pattern descriptor bounds shape edges for providing highly localized distinct features supporting characterization. Then a novel feature representation scheme fabricates these shapes into histograms subsequently, employed for matching and retrieval. The metric Bull's Eye Retrieval (BER) rate is deployed for retrieval analysis on the Kimia-99, MPEG-7 and Tari-1000 datasets that reveal a uniform and remarkable performance higher than 90% over its predecessors. The congruence nature of the L- shaped geometrical arrangement ensures its robustness towards diverse affine transformations and warrants increased performance. The complexity associated with descriptor realization along space and time reveals its lightweight simplicity and efficiency.
Keyword:
Bull ?s eye retrieval
Congruence
Feature representation
Geometry
L -shape derivative
Retrieval
期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
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