Image query by semantical color content

1996 ◽  
Author(s):  
J. M. Corridoni ◽  
A. Del Bimbo ◽  
S. De Magistris
Keyword(s):  
Image Query

Visual image query

2002 ◽  
Author(s):  
Krešimir Matković ◽  
László Neumann ◽  
Johannes Siglaer ◽  
Martin Kompast ◽  
Werner Purgathofer
Keyword(s):  
Visual Image ◽  
Image Query

Hepatic CT image query based on threshold-based classification scheme with gabor features

2008 ◽  
Vol 13 (6) ◽  
pp. 753-758
Author(s):  
Li-jun Jiang ◽  
Yong-xing Luo ◽  
Jun Zhao ◽  
Tian-ge Zhuang
Keyword(s):  
Classification Scheme ◽  
Ct Image ◽  
Gabor Features ◽  
Image Query

Intelligent Content-Based Dermoscopic Image Retrieval with Relevance Feedback for Computer-Aided Melanoma Diagnosis

2017 ◽  
Vol 10 (1) ◽  
pp. 85-108 ◽  
Author(s):  
Khadidja Belattar ◽  
Sihem Mostefai ◽  
Amer Draa
Keyword(s):  
Skin Lesion ◽  
Image Retrieval ◽  
Relevance Feedback ◽  
Query Image ◽  
Melanoma Diagnosis ◽  
Computer Aided ◽  
Histogram Intersection ◽  
Dermoscopic Image ◽  
Image Query ◽  
Aided Diagnosis

The use of Computer-Aided Diagnosis in dermatology raises the necessity of integrating Content-Based Image Retrieval (CBIR) technologies. The latter could be helpful to untrained users as a decision support system for skin lesion diagnosis. However, classical CBIR systems perform poorly due to semantic gap. To alleviate this problem, we propose in this paper an intelligent Content-Based Dermoscopic Image Retrieval (CBDIR) system with Relevance Feedback (RF) for melanoma diagnosis that exhibits: efficient and accurate image retrieval as well as visual features extraction that is independent of any specific diagnostic method. After submitting a query image, the proposed system uses linear kernel-based active SVM, combined with histogram intersection-based similarity measure to retrieve the K most similar skin lesion images. The dominant (melanoma, benign) class in this set will be identified as the image query diagnosis. Extensive experiments conducted on our system using a 1097 image database show that the proposed scheme is more effective than CBDIR without the assistance of RF.

Interactive image query system using progressive transmission

1983 ◽  
Vol 17 (3) ◽  
pp. 323-330 ◽  
Author(s):  
F. S. Hill ◽  
Sheldon Walker ◽  
Fuwen Gao
Keyword(s):  
Progressive Transmission ◽  
Query System ◽  
Image Query
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