Applied combinatorics
A fast algorithm to calculate the Euler number for binary images
Pattern Recognition Letters
Digital image processing
Retrieval of similar pictures on pictorial databases
Pattern Recognition
International Journal of Computer Vision
A survey of moment-based techniques for unoccluded object representation and recognition
CVGIP: Graphical Models and Image Processing
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Image difference threshold strategies and shadow detection
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Wavelet-based image indexing techniques with partial sketch retrieval capability
IEEE ADL '97 Proceedings of the IEEE international forum on Research and technology advances in digital libraries
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
ACM '86 Proceedings of 1986 ACM Fall joint computer conference
Design of Dynamic Data Structures
Design of Dynamic Data Structures
Digital Image Processing
Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
Spatial similarity-based retrievals and image indexing by hierarchical decomposition
IDEAS '97 Proceedings of the 1997 International Symposium on Database Engineering & Applications
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Euler Vector: A Combinatorial Signature for Gray-Tone Images
ITCC '02 Proceedings of the International Conference on Information Technology: Coding and Computing
A pipeline architecture for computing the Euler number of a binary image
Journal of Systems Architecture: the EUROMICRO Journal
Stacked Euler Vector (SERVE): A Gray-Tone Image Feature Based on Bit-Plane Augmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Euler vector for search and retrieval of gray-tone images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Connectivity properties capture a natural spatial feature of a binary image. Albeit they are easy to compute, more often than not, they alone fail to provide a good characterization of the image because of the fact that several different images may have the same connectivity features. Typically, other types of parameters, e.g., moments, are used to augment the connectivity feature for efficient indexing and retrieval purposes. In this work, an alternative approach is proposed. Instead of considering other diverse features, which are computationally intensive, only the connectivity features of the image are used iteratively using a novel concept of spatial masking. For this purpose, a greedy algorithm for constructing a spatial feature vector of variable length for a binary image, is proposed. The algorithm is based on XOR-ing the image bit-plane with a few pseudo-random synthetic masks, and its novelty lies in computing the feature vector iteratively, depending on the size and diversity of the image database. The classical Euler number and the two primary connectivity features from which it is derived, namely, the number of connected components and the number of holes, are used to finally generate a unique feature vector for each binary image in the database using a fuzzy membership function customized for the given database. The method is particularly suitable for large-sized image archives of a digital library, where each image contains one or more objects. It is found to converge within only three iterations for a postal stamp database consisting of 2598 images, and also for a logo database of 1034 images. A data structure called discrimination tree has been introduced for supporting efficient storage and indexing of the images using the above feature vector.