Hierarchical Cellular Tree: An Efficient Indexing Scheme for Content-Based Retrieval on Multimedia Databases

2007 ◽  
Vol 9 (1) ◽  
pp. 102-119 ◽  
Author(s):  
Serkan Kiranyaz ◽  
Moncef Gabbouj
Keyword(s):  
Multimedia Databases ◽  
Content Based Retrieval ◽  
Indexing Scheme

Knowledge-assisted content based retrieval for multimedia databases

1994 ◽  
Vol 1 (4) ◽  
pp. 12-21 ◽  
Author(s):  
A. Yoshitaka ◽  
S. Kishida ◽  
M. Hirakawa ◽  
T. Ichikawa
Keyword(s):  
Multimedia Databases ◽  
Content Based Retrieval

Content-Based Multimedia Retrieval

2009 ◽  
pp. 260-266
Author(s):  
Chia-Hung Wei
Keyword(s):  
Digital Media ◽  
Multimedia Databases ◽  
Multimedia Retrieval ◽  
Subjective Perception ◽  
Content Based Retrieval ◽  
Textual Description ◽  
The Media ◽  
Video And Audio ◽  
Boolean Queries ◽  
Textual Form

In the past decade, there has been rapid growth in the use of digital media, such as images, video, and audio. As the use of digital media increases, retrieval and management techniques become more important in order to facilitate the effective searching and browsing of large multimedia databases. Before the emergence of content-based retrieval, media was annotated with text, allowing the media to be accessed by text-based searching. Through textual description, media is managed and retrieved based on the classification of subject or semantics. This hierarchical structure, like yellow pages, allows users to easily navigate and browse, or search using standard Boolean queries. However, with the emergence of massive multimedia databases, the traditional text-based search suffers from the following limitations (Wei, Li, & Wilson, 2006): Manual annotations require too much time and are expensive to implement. As the number of media in a database grows, the difficulty in finding desired information increases. It becomes infeasible to manually annotate all attributes of the media content. Annotating a 60-minute video, containing more than 100,000 images, consumes a vast amount of time and expense. Manual annotations fail to deal with the discrepancy of subjective perception. The phrase, “an image says more than a thousand words,” implies that the textual description is sufficient for depicting subjective perception. To capture all concepts, thoughts, and feelings for the content of any media is almost impossible. Some media contents are difficult to concretely describe in words. For example, a piece of melody without lyric or irregular organic shape cannot easily be expressed in textual form, but people expect to search media with similar contents based on examples they provided. In an attempt to overcome these difficulties, content- based retrieval employs content information to automatically index data with minimal human intervention.

Embedded lattices tree: An efficient indexing scheme for content based retrieval on image databases

2009 ◽  
Vol 20 (2) ◽  
pp. 145-156 ◽  
Author(s):  
Mahmoud Mejdoub ◽  
Leonardo Fonteles ◽  
Chokri BenAmar ◽  
Marc Antonini
Keyword(s):  
Image Databases ◽  
Content Based Retrieval ◽  
Indexing Scheme
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