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» Evaluating Image Retrieval
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IPCV
2008
15 years 6 months ago
Content Based Retrieval System for Archaeological Images
Most of the existing image retrieval systems take the textual query from the user and utilize the metadata associated with the database images to retrieve the result. However, the...
Akshay Asthana, Ranjan Dutta, Anshul Jain, Deepak ...
VCIP
2003
238views Communications» more  VCIP 2003»
15 years 6 months ago
Texture segmentation based on features in wavelet domain for image retrieval
Texture is a fundamental feature which provides significant information for image classification, and is an important content used in content-based image retrieval (CBIR) system. ...
Ying Liu, Si Wu, Xiaofang Zhou
IVC
2007
176views more  IVC 2007»
15 years 4 months ago
Kernel-based distance metric learning for content-based image retrieval
ct 8 For a specific set of features chosen for representing images, the performance of a content-based image retrieval (CBIR) system 9 depends critically on the similarity or diss...
Hong Chang, Dit-Yan Yeung
CIVR
2007
Springer
231views Image Analysis» more  CIVR 2007»
15 years 11 months ago
Classification of video events using 4-dimensional time-compressed motion features
Among the various types of semantic concepts modeled, events pose the greatest challenge in terms of computational power needed to represent the event and accuracy that can be ach...
Alexander Haubold, Milind R. Naphade
179
Voted
ICIP
2007
IEEE
16 years 6 months ago
Using Phase and Magnitude Information of the Complex Directional Filter Bank for Texture Image Retrieval
This paper discusses how to utilize both magnitude and phase information obtained from the complex directional lter bank (CDFB) for the purpose of texture image retrieval. The rel...
An P. N. Vo, Soontorn Oraintara, Truong T. Nguyen