A survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video

By Sameer Kiran Antani, Rangachar Kasturi, Ramesh C. Jain. Pattern Recognition, 2002

383 citations recorded by the source corpus.

The need for content-based access to image and video information from media archives has captured the attention of researchers in recent years. Research e0orts have led to the development of methods that provide access to image and video data. These methods have their roots in pattern recognition. The methods are used to determine the similarity in the visual information content extracted from low level features. These features are then clustered for generation of database indices. This paper presents a comprehensive surveyon the use of these pattern recognition methods which enable image and video retrieval bycontent. ? 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/950d56ca43b56e78da79f4ed07d5448ed80475b6

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In Computer Vision and Pattern Recognition

Citations in the corpus

Features for image retrieval: an experimental comparison (2008, background): “Obviously, object recognition and CBIR are closely related fields [63, 64] and for some clearly defined retrieval tasks, object recognition methods might actually be the only possible solution: e.”
Lung Segmentation in Chest Radiographs Using Anatomical Atlases With Nonrigid Registration (2013, neutral): “CBIR systems are designed to be fast for online retrieval applications with an offline preprocessing step to extract signature features for each image in the database [37]–[39] and can incorporate multimodal information to improve precision [40].”
Histology image analysis for carcinoma detection and grading (2012, methodology): “In feature similarity computation, a number of metrics [3,11,44] can be applied besides the commonly used Euclidean distance, such as Mahalanobis and Chebyshev distances.”
A survey of content-based image retrieval with high-level semantics (2007, background): “fields (Vailaya et al. 2001; Antani et al. 2002) and for some clearly defined retrieval tasks, object recognition methods might actually be the only possible solution: e.”