نتایج جستجو برای: text line detection

تعداد نتایج: 1105421  

2011
Xiaojun Du

Image Segmentation and Its Applications Based on the Mumford-Shah Model Xiaojun Du, Ph.D. Concordia University, 2011 Image segmentation is an important topic in computer vision and image processing. As a region-based (global) approach, the Mumford and Shah (MS) model is a powerful and robust segmentation technique as compared to edge-based (local) methods. In this thesis we apply the MS model t...

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2008
Pei-Ju Chiang Aravind K. Mikkilineni Sungjoo Suh Edward J. Delp Jan P. Allebach George T.-C. Chiu

Printer identification based on printed documents can provide forensic information to protect copyright and verify authenticity. In addition to intrinsic features (intrinsic signatures) of the printer, modulating the printing process to embed specific signature (extrinsic signatures) will further extend the encoding capacity. In this paper we describe the use of laser modulation in electrophoto...

2003
Juan Manuel Alonso-Weber Inés María Galván Araceli Sanchis

. Different authors have developed modifications of the Kohonen Self-Organizing Maps to solve known combinatorial optimization problems. In this paper a modification of the Kohonen Map is proposed to solve the detection of white inter-text spaces in a digitized plain text documents. The idea relies on the fact that line extraction problem has several features which match easily with Kohonen net...

2016
Sijia Liu Yanshan Wang Saeed Mehrabi Dingcheng Li Hongfang Liu

In this working note, we introduce our participation at the ImageCLEF 2016 Handwritten Document Retrieval Task. We mainly focused on hyphenation detection using line images and information retrieval using n-best results. The hyphenation detection step utilizes extracted image features from beginning and end of a line and a binary classifier to determine if a line contains hyphenation. Then the ...

Journal: :Baghdad Science Journal 2008

Journal: :Behavior Research Methods & Instrumentation 1974

Journal: :International Journal of Data Mining & Knowledge Management Process 2014

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