System for screening objectionable images using Daubechies' wavelets and color histograms

1997 ◽  
pp. 20-30 ◽  
Author(s):  
James Ze Wang ◽  
Gio Wiederhold ◽  
Oscar Firschein
Keyword(s):  
Daubechies Wavelets ◽  
Color Histograms

On the computation of scaling coefficients of Daubechies' wavelets

2004 ◽  
Vol 2 (3) ◽  
pp. 399-419 ◽  
Author(s):  
Dana Černá ◽  
Václav Finěk
Keyword(s):  
Daubechies Wavelets

The optimal coefficients in Daubechies wavelets

1992 ◽  
Vol 60 (1-4) ◽  
pp. 239-244 ◽  
Author(s):  
Gilbert Strang
Keyword(s):  
Daubechies Wavelets ◽  
Optimal Coefficients

scholarly journals Representation of plane elastostatics operators in daubechies wavelets

1996 ◽  
Vol 60 (4) ◽  
pp. 561-569 ◽  
Author(s):  
S. Dumont ◽  
F. Lebon
Keyword(s):  
Daubechies Wavelets ◽  
Plane Elastostatics

scholarly journals STUDYING THE INFLUENCE OF THE NUMBER VANISHING MOMENTS OF DAUBECHIES WAVELETS FOR THE ANALYSIS OF MICROSTRIP LINES

2016 ◽  
Vol 62 ◽  
pp. 57-64
Author(s):  
Mohamed Bayjja ◽  
Mohamed Boussouis ◽  
Naima Amar Touhami
Keyword(s):  
Daubechies Wavelets ◽  
Vanishing Moments ◽  
Microstrip Lines

Stereo-camera-based object detection using fuzzy color histograms and a fuzzy classifier with depth and shape estimations

2016 ◽  
Vol 46 ◽  
pp. 753-766 ◽  
Author(s):  
Chia-Feng Juang ◽  
Guo-Cyuan Chen ◽  
Chung-Wei Liang ◽  
Demei Lee
Keyword(s):  
Object Detection ◽  
Fuzzy Classifier ◽  
Stereo Camera ◽  
Color Histograms

Musculoskeletal ultrasound image denoising using Daubechies wavelets

2012 ◽  
Author(s):  
Rishu Gupta ◽  
I. Elamvazuthi ◽  
P. Vasant
Keyword(s):  
Image Denoising ◽  
Ultrasound Image ◽  
Musculoskeletal Ultrasound ◽  
Daubechies Wavelets

VIDEO CONTENT REPRESENTATION FOR SHOT RETRIEVAL AND SCENE EXTRACTION

2001 ◽  
Vol 01 (03) ◽  
pp. 507-526 ◽  
Author(s):  
TONG LIN ◽  
HONG-JIANG ZHANG ◽  
QING-YUN SHI
Keyword(s):  
Similarity Measure ◽  
Video Content ◽  
Object Based ◽  
Scene Structure ◽  
Color Histograms ◽  
Extraction Algorithm ◽  
Content Representation ◽  
Video Shot ◽  
Shot Boundary ◽  
Spatio Temporal

In this paper, we present a novel scheme on video content representation by exploring the spatio-temporal information. A pseudo-object-based shot representation containing more semantics is proposed to measure shot similarity and force competition approach is proposed to group shots into scene based on content coherences between shots. Two content descriptors, color objects: Dominant Color Histograms (DCH) and Spatial Structure Histograms (SSH), are introduced. To represent temporal content variations, a shot can be segmented into several subshots that are of coherent content, and shot similarity measure is formulated as subshot similarity measure that serves to shot retrieval. With this shot representation, scene structure can be extracted by analyzing the splitting and merging force competitions at each shot boundary. Experimental results on real-world sports video prove that our proposed approach for video shot retrievals achieve the best performance on the average recall (AR) and average normalized modified retrieval rank (ANMRR), and Experiment on MPEG-7 test videos achieves promising results by the proposed scene extraction algorithm.

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