✦ LIBER ✦

Sketch-Based Image Queries in Topographic Databases

✍ Scribed by Peggy Agouris; Anthony Stefanidis; James D Carswell

Publisher: Elsevier Science
Year: 1999
Tongue: English
Weight: 387 KB
Volume: 10
Category: Article
ISSN: 1047-3203
DOI: 10.1006/jvci.1999.0414

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper we present the development of a system prototype for sketch-based queries for the content-based retrieval of digital images from topographic databases. We discuss our overall strategy and associated algorithmic and implementation aspects, and we present associated database design issues. The query tools devised in this research are employing user-provided sketches of the shape and spatial configuration of the object(s) which should appear in the images to be retrieved. Our matching tool is inspired by least-squares matching (lsm) and represents an extension of lsm to function with a variety of raster representations. Our strategy makes use of a hierarchical organization of feature shapes within a feature library. The results are ranked according to statistical scores and the user can subsequently narrow or broaden his/her search according to the previously obtained results and the purpose of the search. Our approach combines the design of an integrated database environment with the development of a feature library and the necessary matching tools. We discuss our overall strategy and individual database components and present some implementation results.

📜 SIMILAR VOLUMES

An Indexing and Retrieval Mechanism for

An Indexing and Retrieval Mechanism for Complex Similarity Queries in Image Databases

✍ Guang-Ho Cha; Chin-Wan Chung 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 563 KB

A content-based image retrieval mechanism to support complex similarity queries is presented. The image content is defined by three kinds of features: quantifiable features describing the visual information, nonquantifiable features describing the semantic information, and keywords describing more a

SEMCOG: A hybrid object-based image and

SEMCOG: A hybrid object-based image and video database system and its modeling, language, and query processing

✍ Li, Wen-Syan; Candan, K. Sel�uk 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 326 KB 👁 2 views

Multimedia data types, such as image and video, are structurally more complex than traditional data types. We view an image as a compound object containing many sub-objects. Each sub-object corresponds to image regions that are visually and semantically meaningful (e.g., car, man, etc.). In this pap

Document image binarization based on top

Document image binarization based on topographic analysis using a water flow model

✍ In-Kwon Kim; Dong-Wook Jung; Rae-Hong Park 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 989 KB

This paper proposes a local adaptive thresholding method based on a water #ow model, in which an image surface is considered as a three-dimensional (3-D) terrain. To extract characters from backgrounds, we pour water onto the terrain surface. Water #ows down to the lower regions of the terrain and "

ASSERT: A Physician-in-the-Loop Content-

ASSERT: A Physician-in-the-Loop Content-Based Retrieval System for HRCT Image Databases

✍ Chi-Ren Shyu; Carla E. Brodley; Avinash C. Kak; Akio Kosaka; Alex M. Aisen; Lynn 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 574 KB

It is now recognized in many domains that content-based image retrieval from a database of images cannot be carried out by using completely automated approaches. One such domain is medical radiology for which the clinically useful information in an image typically consists of gray level variations i

Intermediate Annotationless Dynamical Ob

Intermediate Annotationless Dynamical Object-Index-Based Query in Large Image Archives with Holographic Representation

✍ Javed I. Khan 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 800 KB

This paper presents a new parallel and distributed associative network-based technique for content-based image retrieval denoted by a set of pixels. It is expected that a match (CBIR) with dynamic indices. Unlike any prior artificial assoshould be based on the similarity between these objects. ## c