On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of image registration techniques
ACM Computing Surveys (CSUR)
A linear algorithm for incremental digital display of circular arcs
Communications of the ACM
Geometric Hashing: An Overview
IEEE Computational Science & Engineering
Finding faces in cluttered scenes using random labeled graph matching
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
The Feature Extraction of Chinese Character Based on Contour Information
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Algorithm for computer control of a digital plotter
IBM Systems Journal
Translation, rotation, and scale-invariant object recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Rotation Moment Invariants for Recognition of Symmetric Objects
IEEE Transactions on Image Processing
Multi-source Airborne IR and Optical Image Fusion and Its Application to Target Detection
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
GPU accelerated real time rotation, scale and translation invariant image registration method
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Efficient and robust shape retrieval from deformable templates
ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: applications and case studies - Volume Part II
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs
Journal of Visual Communication and Image Representation
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In this paper, we consider the grayscale template-matching problem, invariant to rotation, scale, translation, brightness and contrast, without previous operations that discard grayscale information, like detection of edges, detection of interest points or segmentation/binarization of the images. The obvious "brute force" solution performs a series of conventional template matchings between the image to analyze and the template query shape rotated by every angle, translated to every position and scaled by every factor (within some specified range of scale factors). Clearly, this takes too long and thus is not practical. We propose a technique that substantially accelerates this searching, while obtaining the same result as the original brute force algorithm. In some experiments, our algorithm was 400 times faster than the brute force algorithm. Our algorithm consists of three cascaded filters. These filters successively exclude pixels that have no chance of matching the template from further processing.