On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Querying by color regions using VisualSEEk content-based visual query system
Intelligent multimedia information retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
A Wavelet-Based Image Indexing, Clustering, and Retrieval Technique Based on Edge Feature
WAA '01 Proceedings of the Second International Conference on Wavelet Analysis and Its Applications
NeTra: a toolbox for navigating large image databases
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Image Retrieval from the World Wide Web: Issues, Techniques, and Systems
ACM Computing Surveys (CSUR)
Multiscale Fourier Descriptor for Shape-Based Image Retrieval
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Edge-Based Rich Representation for Vehicle Classification
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Content-based image retrieval: approaches and trends of the new age
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Perceptual Shape-Based Natural Image Representation and Retrieval
ICSC '07 Proceedings of the International Conference on Semantic Computing
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
A Framework for Edge Detection and Linking Using Wavelets and Image Fusion
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 1 - Volume 01
Edge Detection Based on Wavelet Analysis with Gaussian Filter
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
Trademark Image Retrieval Using Wavelet-based Shape Features
IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
Scale-invariant shape features for recognition of object categories
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
PicToSeek: combining color and shape invariant features for image retrieval
IEEE Transactions on Image Processing
Rotation Moment Invariants for Recognition of Symmetric Objects
IEEE Transactions on Image Processing
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Since shape is one of the important low level features of any Content Based Image Retrieval (CBIR) system, this paper proposes a new edge based shape feature representation method with multiresolution enhanced orthogonal polynomials model and morphological operations for effective image retrieval. In the proposed method, initially the orthogonal polynomials model coefficients are computed and reordered into multiresolution subband like structure. Edge image is then obtained by utilizing the two level adaptive thresholds and local maxima of the gradient in horizontal, vertical, diagonal and anti-diagonal directions. The approximate shape boundary of the image is recovered with morphological operations. Then the Pseudo Zernike moment based global shape features, which are invariant to basic geometric transformations, are extracted. The obtained features are termed as global shape feature vector and are used for retrieving similar images with Canberra distance metric. The efficiency of the proposed method is experimented on a subset of standard Corel, Yale and MPEG-7 databases and the results are compared with existing techniques.