Results 281 to 290 of about 259,759 (314)

On Image Enhancement for Unsupervised Image Description and Matching

2019
An image enhancer improves the visibility and readability of the content of any input image by modifying one or more features related to vision perception. Its performance is usually assessed by quantifying and comparing the level of these features in the input and output images and/or with respect to a gold standard, often regardless of the ...
Michela Lecca, Alessandro Torresani, Fabio Remondino   +2 more
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Pattern matching image compression

Proceedings of Data Compression Conference - DCC '96, 2002
We propose a non-transform image compression scheme based on approximate pattern matching, that we name pattern matching linage compression (PMIC). The main idea behind it is a lossy extension of the Lempel-Ziv data compression scheme in which one searches for the longest prefix of an uncompressed image that approximately occurs in the already ...
Mikhail J. Atallah, Yann Génin, Wojciech Szpankowski   +2 more
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Matching stereo satellite images

[1992] Proceedings. 11th IAPR International Conference on Pattern Recognition, 2003
Stereo SPOT satellite images were matched by extracting and then matching linear features. The features were extracted by grouping pixels into regions upon similar gradient orientation. Lines are fitted to regions and parameters calculated providing a rich set of attributes, which are then used to match corresponding features in the stereo images. >
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Hierarchical matching of panoramic images

12th International Conference on Image Analysis and Processing, 2003.Proceedings., 2004
When matching regions from "similar" images, one typically has the problem of missing counterparts due to local or even global variations of segmentation fineness. Matching segmentation hierarchies, however, not only increases the chances of finding counterparts, but also allows us to exploit the manifold constraints coming from the topological ...
GLANTZ R, PELILLO, Marcello, KROPATSCH W. G.   +2 more
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Tattoo Image Matching and Retrieval

Computer, 2012
An automated tattoo image matching system achieves significantly better results for forensic and law enforcement applications than traditional keyword-based matching.
Anil K. Jain 0001, Rong Jin 0001, Jung-Eun Lee   +2 more
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Contour Matching in Omnidirectional Images

2007
This paper presents a novel method for contour matching in the architectural scenes captured by the omnidirectional camera. Since most line segments of man-made objects are projected to lines and contours, contour matching problem is important for 3D analysis in an omnidirectional indoor scene.
Yong Ho Hwang, Jaeman Lee, Hyun-Ki Hong
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Pattern matching in a digitized image

Algorithmica, 1994
The continuous pattern matching problem is defined. Given are two pictures, each consisting of unicolor regions; one picture is called the scene and the other the pattern. The problem is to find all occurrences of the pattern in the scene. As a step towards efficient algorithmic handling of the continuous pattern matching problem by computers, where ...
Gad M. Landau, Uzi Vishkin
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Color matching for image retrieval

Pattern Recognition Letters, 1995
Abstract Color is an important attribute for image matching and retrieval. We present two new color matching methods, the “Reference Color Table Method” and a “Distance Method”, for image retrieval. Both these methods and an existing method “Histogram Intersection” were implemented and tested for a database size of 170 color images.
Babu M. Mehtre, Mohan S. Kankanhalli, Arcot Desai Narasimhalu, Guo Chang Man   +3 more
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Image steganography by wavelet matching

Journal of Electronic Imaging, 2009
We introduce a new steganography method for embedding message bits into images by utilizing the mathematical relation between the image and transformation domains. The proposed method matches the message bit sequences with the coefficients of the discrete Haar wavelet transformation (DHWT) by modifying the pixels related to those coefficients.
Nafiz Arica, Ömer Kurtuldu
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Image understanding and graph matching

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
We show that one of the key problems in Image Understanding is the matching of two symbolic structures, a model and the result of a segmentation. These symbolic structures are conveniently represented as labeled graphs and we present on two examples a formalism which can deal with the inexact or fuzzy matching of such structures in a highly parallel ...
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