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Automatic Registration of Serial Cerebral Angiography: A Comparative Review Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Specific Document Sign Location Detection Based on Point Matching and Clustering

Author : Huaixin Xiong

Published in: Advances in Visual Computing

Publisher: Springer International Publishing

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Abstract

In this paper we describe a method for specific document sign location detection based on key point grouping correspondence. The proposed method extracts stable points determined only by each contour shape as key points, match point pairs based on contour Fourier shape descriptor; clusters point pairs into different scale level set and finally detects sign location by finding projective matrix in each point pairs set. The contribution of this paper includes 1. a novel concept of key point and its extraction method, 2. a clustering operation for grouping point pairs. 3. a fuzzy DBSCAN processing which response to the constraints of maximum clustering radius. The experimental results show that our method is effective way to process printing/scanning document sign detection, both in recall rate and in speed.

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Metadata
Title
Specific Document Sign Location Detection Based on Point Matching and Clustering
Author
Huaixin Xiong
Copyright Year
2018
Book
Advances in Visual Computing

Print ISBN: 978-3-030-03800-7

Electronic ISBN: 978-3-030-03801-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-03801-4_17

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