A note on binary template matching

Tubbs, J. D.

doi:10.1016/0031-3203(89)90045-9

Cited by 102 publications

(50 citation statements)

References 7 publications

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“…The authors conclude about some close relationships among several measures. In the DIA field, the common used measures [3], [4], [5] are the IP , Jaccard, DICE, RU SS, KU L, Hamming, SM , RT , CORR and the Y ule ones (Table I). Taxonomy of the measures is discussed in these different papers.…”

Section: Binary Similarity Measuresmentioning

confidence: 99%

“…Here, the goal is to improve performance by optimizing the similarity measure rather than distance. The weights can be obtained using an optimization method such as genetic algorithms, or assigned to matches according to their relative frequency of occurrence [3]. The typical similarity measures with weighting are the weighted inner product S W IP or the weighted Hamming D W H .…”

Section: Binary Similarity Measuresmentioning

confidence: 99%

“…This paper will present an extended discussion of [3] about the binary template matching problem. The paper in [3] is focussed on the generalization aspects of binary template matching.…”

Section: Introductionmentioning

confidence: 99%

“…The paper in [3] is focussed on the generalization aspects of binary template matching. Here, binary template matching will be mainly discussed in terms of characterization of similarity measures, performance evaluation and optimization issues.…”

Section: Introductionmentioning

confidence: 99%

“…An usual approach in DIA is to convert gray-level images to binary by thresholding. Here, binary template matching can be applied [3]. Although binary template matching has been studied extensively since the early days of pattern recognition, this technique seems not longer in use in the DIA community.…”

Section: Introductionmentioning

confidence: 99%

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Fast and Optimal Binary Template Matching Application to Manga Copyright Protection

Delalandre

Iwata

Kise

2014

2014 11th IAPR International Workshop on Document Analysis Systems

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Abstract-Template matching is a technique used in classifying an object by comparing portions of images with another image. Finding a given template in an image is typically performed by scanning the image and evaluating the similarity with the template. When the scanning is concerned with the entire image template matching is optimal. This paper considers a special case of template matching where the templates are binary. Although binary template matching has been studied extensively since the early days of pattern recognition, this technique seems not longer in use in Document Image Analysis (DIA). The major reasons are the time complexity, the no-invariance to scale and rotation and the lack of adaptability of similarity measures. However, different contributions have been investigated during the last years to improve these aspects: robustness and discrimination capability of similarity measures, their characterization, time-processing optimization with hardware support, etc. In this paper, we will review first some of the recent issues about binary template matching. We will present then a system exploiting bitwise operators and parallel processing supporting fast and accurate binary template matching for Manga copyright protection. This system is compared to a FFT-based template matching, and it outperforms both in processing-time and detection accuracy.

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Section: Binary Similarity Measuresmentioning

confidence: 99%

Section: Binary Similarity Measuresmentioning

confidence: 99%

“…This paper will present an extended discussion of [3] about the binary template matching problem. The paper in [3] is focussed on the generalization aspects of binary template matching.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fast and Optimal Binary Template Matching Application to Manga Copyright Protection

Delalandre

Iwata

Kise

2014

2014 11th IAPR International Workshop on Document Analysis Systems

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A multiple feature/resolution approach to handprinted digit and character recognition

Favata

Srikantan

1996

Int. J. Imaging Syst. Technol.

108

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This article outlines the philosophy, design, and implementation of the Gradient, Structural, Concavity (GSC) recognition algorithm, which has been used successfully in several document reading applications. The GSC algorithm takes a quasi-multiresolution approach to feature generation; that is, several distinct feature types are applied at different scales in the image. These computed features measure the image characteristics at local, intermediate, and large scales. The local-scale features measure edge curvature in a neighborhood of a pixel, the intermediate features measure short stroke types which span several pixels, and the large features measure certain concavities which can span across the image. This philosophy, when coupled with the k-nearest neighbor classification paradigm, results in a recognizer which has both high accuracy and reliable confidence behavior. The confidences computed by this algorithm are generally high for valid class objects and low for nonclass objects. This allows it to be used in document reading algorithms which search for digit or character strings embedded in a field of objects. Applications of this paradigm to off-line digit string recognition and handwritten word recognition are discussed. Tests of the GSC classifier on large data bases of digits and characters are reported. 0 1996 John Wiley & Sons, Inc.A. Gradient Features. The gradient features are computed by convolving two 3 X 3 Sobel operators on the binary image. These operators approximate the x and y derivatives in the image at a pixel position (Fig. 2). The gradient of a center pixel is computed

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Energy‐Efficient Pattern Recognition for Wireless Sensor Networks

Baqer

Khan

2010

Mobile Intelligence

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A note on binary template matching

Cited by 102 publications

References 7 publications

Fast and Optimal Binary Template Matching Application to Manga Copyright Protection

Fast and Optimal Binary Template Matching Application to Manga Copyright Protection

A multiple feature/resolution approach to handprinted digit and character recognition

Energy‐Efficient Pattern Recognition for Wireless Sensor Networks

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