mCLOVER: mobile content-based leaf image retrieval system
Proceedings of the 13th annual ACM international conference on Multimedia
Utilizing venation features for efficient leaf image retrieval
Journal of Systems and Software
A similarity-based leaf image retrieval scheme: Joining shape and venation features
Computer Vision and Image Understanding
Combination of accumulated motion and color segmentation for human activity analysis
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Leaf classification using navigation-based skeletons
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
PDA plant search system based on the characteristics of leaves using fuzzy function
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Supervised locally linear embedding for plant leaf image feature extraction
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Plant species identification using leaf image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
On the convergence of planar curves under smoothing
IEEE Transactions on Image Processing
Leaves shape classification using curvature and fractal dimension
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Automatic identification approach for sea surface bubbles detection
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
A parametric active polygon for leaf segmentation and shape estimation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
A venation-based leaf image classification scheme
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Review: Plant species identification using digital morphometrics: A review
Expert Systems with Applications: An International Journal
A shape-based retrieval scheme for leaf images
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Plant classification based on multilinear independent component analysis
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Advanced shape context for plant species identification using leaf image retrieval
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Two-Dimensional locality discriminant projection for plant leaf classification
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
A shape-based approach for leaf classification using multiscaletriangular representation
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Understanding leaves in natural images - A model-based approach for tree species identification
Computer Vision and Image Understanding
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We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The curvature scale space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the curvature scale space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the curvature scale space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.