资源介绍
James Cope, Thibaut Beghin, Paolo Remagnino, Sarah Barman.
The colour images are not included in this submission.
The Leaves were collected in the Royal Botanic Gardens, Kew, UK.
email: james.cope '@' kingston.ac.uk
This dataset consists of work carried out by James Cope, Charles Mallah, and James Orwell. Kingston University London.
Donor of database Charles Mallah: charles.mallah '@' kingston.ac.uk; James Cope: james.cope '@' kingston.ac.uk
Data Set Information:
For Each feature, a 64 element vector is given per sample of leaf. These vectors are taken as a contigous descriptors (for shape) or histograms (for texture and margin).
Attribute Information:
For Each feature, a 64 element vector is given per sample of leaf. One file for each 64-element feature vectors. Each row begins with the class label. The remaining 64 elements is the feature vector.
Relevant Papers:
This is a new data set, provisional paper: 'Plant Leaf Classification Using
Probabilistic Integration of Shape, Texture and Margin Features' at SPPRA 2013. Authors:
Charles Mallah, James Cope, and James Orwell or Kingston University London.
Previous parts of the data set relate to feature extraction of leaves from:
J. Cope, P. Remagnino, S. Barman, and P. Wilkin.
Plant texture classification using gabor cooccurrences.
Advances in Visual Computing,
pages 669a€“677, 2010.
T. Beghin, J. Cope, P. Remagnino, and S. Barman.
Shape and texture based plant leaf classification. In
Advanced Concepts for Intelligent Vision Systems,
pages 345a€“353. Springer, 2010.
Citation Request:
Charles Mallah, James Cope, James Orwell. Plant Leaf Classification Using Probabilistic Integration of Shape, Texture and Margin Features. Signal Processing, Pattern Recognition and Applications, in press. 2013.
