Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
A retrieval technique for similar shapes
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Pattern recognition with moment invariants: a comparative study and new results
Pattern Recognition
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Constraint query algebras
Optimal multi-step k-nearest neighbor search
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Multidimensional access methods
ACM Computing Surveys (CSUR)
Digital Image Processing
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Querying Time Series Data Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
A Database for Handwritten Text Recognition Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Feature-Based Retrieval of Similar Shapes
Proceedings of the Ninth International Conference on Data Engineering
Fast Nearest Neighbor Search in Medical Image Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On Similarity Queries for Time-Series Data: Constraint Specification and Implementation
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Using extended feature objects for partial similarity retrieval
The VLDB Journal — The International Journal on Very Large Data Bases
Fourier transform based techniques in efficient retrieval of similar time sequences
Fourier transform based techniques in efficient retrieval of similar time sequences
WARP: Accurate Retrieval of Shapes Using Phase of Fourier Descriptors and Time Warping Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation invariant indexing of shapes and line drawings
Proceedings of the 14th ACM international conference on Information and knowledge management
Exploring movement-similarity analysis of moving objects
SIGSPATIAL Special
A fuzzy set approach for shape-based image annotation
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Fuzzy image labeling by partially supervised shape clustering
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Affine invariant gradient based shape descriptor
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Visually exploring movement data via similarity-based analysis
Journal of Intelligent Information Systems
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We propose an indexing technique for the fast retrieval of objects in 2D images based on similarity between their boundary shapes. Our technique is robust in the presence of noise and supports several important notions of similarity including optimal matches irrespective of variations in orientation and/or position. Our method can also handle size-invariant matches using a normalization technique, although optimality is not guaranteed here. We implemented our method and performed experiments on real (hand-written digits) data. Our experimental results showed the superiority of our method compared to search based on sequential scanning, which is the only obvious competitor. The performance gain of our method increases with any increase in the number or the size of shapes.