Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Leaf Image Retrieval with Shape Features
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
Matching shapes with self-intersections: application to leaf classification
IEEE Transactions on Image Processing
A similarity-based leaf image retrieval scheme: Joining shape and venation features
Computer Vision and Image Understanding
iScope: personalized multi-modality image search for mobile devices
Proceedings of the 7th international conference on Mobile systems, applications, and services
A content based image retrieval system for a biological specimen collection
Computer Vision and Image Understanding
A venation-based leaf image classification scheme
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Client-Side Relevance Feedback Approach for Image Retrieval in Mobile Environment
International Journal of Multimedia Data Engineering & Management
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This demonstration presents a content-based leaf image retrieval system that supports wired/wireless access. For example, if we want to know about a plant that we encounter in a mountain or field, we might look it up in an illustrated book. But, it will take a long time to search due to the lack of appropriate indexing or search clues and huge amounts of similar plants. In order to solve this problem, we developed a content-based leaf image retrieval system called mCLOVER that supports both wired and wireless access and includes a set of novel features for easy querying and efficient retrieval.