New Feature Descriptors for Content Based Image Retrieval

K. Prasanthi Jasmine

ISBN 10: 6202919418 / ISBN 13: 9786202919418

Published by LAP LAMBERT Academic Publishing Okt 2020, 2020

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -The proliferation of high quality and economical image sensors has precipitated renewed interest in the research community for developing efficient techniques to handle a large database. The concept of image retrieval came into existence and has been an active area of research aimed at addressing two major issues viz., database management and computer vision.The visual content descriptors are either global or local. A global descriptor represents the visual features of the whole image, whereas a local descriptor represents the visual features of regions or objects to describe the image. Further, these are subdivided into two categories, spatial and transform domain-based features. The approach makes use of pixels (a group of adjacent pixels) or gray values and the other makes use of transformed data of the gray image for feature calculation. 228 pp. Englisch.

Seller Inventory # 9786202919418

Bibliographic Details

• Title: New Feature Descriptors for Content Based Image Retrieval
• Publisher: LAP LAMBERT Academic Publishing Okt 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 6202919418
• ISBN 13: 9786202919418
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 14D millimeters 220 millimeters width by 150 millimeters height by 14 millimeters depth
• Weight: 358 grams

About this title

Synopsis

The proliferation of high quality and economical image sensors has precipitated renewed interest in the research community for developing efficient techniques to handle a large database. The concept of image retrieval came into existence and has been an active area of research aimed at addressing two major issues viz., database management and computer vision.The visual content descriptors are either global or local. A global descriptor represents the visual features of the whole image, whereas a local descriptor represents the visual features of regions or objects to describe the image. Further, these are subdivided into two categories, spatial and transform domain-based features. The approach makes use of pixels (a group of adjacent pixels) or gray values and the other makes use of transformed data of the gray image for feature calculation.