Titlebook: Image Description and Retrieval; Enrico Vicario Book 1998 Plenum Press, New York 1998 databases.information.information system.modeling.mu

Oratory

Hearten

Efficient and Effective Nearest Neighbor Search in a Medical Image Database of Tumor Shapes,no false dismissals for range queries. In addition, we present a nearest neighbor algorithm that also guarantees no false dismissals..We implemented the method and tested it against a testbed of realistic tumor shapes generated by an established tumor-growth model [12]. The response time of our meth

BRACE

Shape-Similarity-Based Retrieval in Image Databases, shape in an image by a character string. A trie-based multilevel structure is employed to organize the shape descriptions and to efficiently search the database for shapes that are qualitatively similar to a query shape.

BUDGE

Color Angular Indexing and Image Retrieval,ose that image similarity might be measured in an analogous manner. This hypothesis is tested using two image sets: Swain’s object database (pictures of single objects on black backgrounds) and Healey and Wang ’s texture images (natural textures such as sky and forest viewed under different imaging

享樂(lè)主義者

harangue

Induction

Shape-Similarity-Based Retrieval in Image Databases, be resolved in the design of a shape similarity-based retrieval approach are discussed. Two different techniques for similar shape retrieval are presented..The first technique, called Feature-Index-Based Similar Shape Retrieval (FIBSSR), is for the 2-dimensional shape retrieval problem. It represen

Thyroiditis

GIDDY

Indexing Color-Texture Image Patterns,rmal color space as their color difference measure, and then describe such differences using low-order spatial moments. Experimental results on a database of images of random color textures confirm the feasibility of our approach, which outperforms more standard procedures in retrieval accuracy and

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