Morphological features for leaf based plant recognition
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Date
2013
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE Computer Society
Abstract
Although plant recognition has become an increasingly popular research topic, it remains nonetheless a scientific and technical challenge. Besides all the difficulties of classic object recognition, such as illumination, viewpoint and scale variations, plants can additionally exhibit visual changes depending on their age and condition, thus demanding a specialized approach. In this paper, we present two descriptors based on mathematical morphology; the first consists of the computation of morphological covariance on the leaf contour profile and the second is an extension of the recently introduced circular covariance histogram, capturing leaf venation characteristics. The effectiveness of both descriptors has been validated with the ImageClef'12 plant identification dataset. © 2013 IEEE.
Description
The Institute of Electrical and Electronics Engineers (IEEE) Signal Processing Society
Keywords
circular covariance histogram, feature extraction, mathematical morphology, morphological covariance, Plant recognition
Turkish CoHE Thesis Center URL
Citation
39
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N/A
Scopus Q
N/A
Source
2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings -- 2013 20th IEEE International Conference on Image Processing, ICIP 2013 -- 15 September 2013 through 18 September 2013 -- Melbourne, VIC -- 115163
Volume
Issue
Start Page
1496
End Page
1499