Title :
Recognition of whole and deformed plant leaves using statistical shape features and neuro-fuzzy classifier
Author :
Chaki, Jyotismita ; Parekh, Ranjan ; Bhattacharya, Samar
Author_Institution :
Sch. of Educ. Technol., Jadavpur Univ., Kolkata, India
Abstract :
This paper proposes a methodology for recognition of plant species by using a set of statistical features obtained from digital leaf images. As the features are sensitive to geometric transformations of the leaf image, a pre processing step is initially performed to make the features invariant to transformations like translation, rotation and scaling. Images are classified to 32 pre-defined classes using a Neuro fuzzy classifier. Comparisons are also done with Neural Network and k-Nearest Neighbor classifiers. Recognizing the fact that leaves are fragile and prone to deformations due to various environmental and biological factors, the basic technique is subsequently extended to address recognition of leaves with small deformations. Experimentations using 640 leaf images varying in shape, size, orientations and deformations demonstrate that the technique produces acceptable recognition rates.
Keywords :
biology computing; botany; feature extraction; fuzzy neural nets; geometry; image classification; shape recognition; statistical analysis; biological factors; deformed plant leaf recognition; digital leaf images; environmental factors; geometric transformations; image rotation; image scaling; image translation; k-nearest neighbor classifiers; leaf deformations; leaf orientations; leaf shape; leaf size; neural network; neuro-fuzzy classifier; plant species recognition; statistical shape features; whole plant leaf recognition; Accuracy; Biology; Feature extraction; Image recognition; Image segmentation; Shape; Training; deformed leaf classification; neuro-fuzzy classifier; plant leaf recognition; statistical shape features;
Conference_Titel :
Recent Trends in Information Systems (ReTIS), 2015 IEEE 2nd International Conference on
Conference_Location :
Kolkata
DOI :
10.1109/ReTIS.2015.7232876