Combining interest points and edges for content-based image retrieval

This paper presents a novel approach using combined features to retrieve images containing specific objects, scenes or buildings. The content of an image is characterized by two kinds of features: Harris-Laplace interest points described by the SIFT descriptor and edges described by the edge color histogram. Edges and corners contain the maximal amount of information necessary for image retrieval. The feature detection in this work is an integrated process: edges are detected directly based on the Harris function; Harris interest points are detected at several scales and Harris-Laplace interest points are found using the Laplace function. The combination of edges and interest points brings efficient feature detection and high recognition ratio to the image retrieval system. Experimental results show this system has good performance. © 2005 IEEE.

Combining Plant Pathogenic Fungi and the Leaf-Mining Fly, Hydrellia pakistanae, Increases Damage to Hydrilla

Four fungal species, F71PJ Acremonium sp., F531 Cylindrocarpon sp., F542, Botrytis sp., and F964 Fusarium culmorum [Wm. G. Sm.] Sacc. were recovered from hydrilla [ Hydrilla verticillata (L. f.) Royle] shoots or from soil and water surrounding hydrilla growing in ponds and lakes in Florida and shown to be capable of killing hydrilla in a bioassay. The isolates were tested singly and in combination with the leaf-mining fly, Hydrellia pakistanae (Diptera: Ephydridae), for their capability to kill or severely damage hydrilla in a bioassay.