Mathematical Imaging: Theory and Applications

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 2085

Special Issue Editor


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Guest Editor
School of Computer Science, The Academic College of Tel Aviv-Yaffo, POB 8401, Tel Aviv 61083, Israel
Interests: machine learning; pattern recognition; computer vision; document image analyzing; image processing

Special Issue Information

Dear Colleagues,

Digital image analysis is the science of extracting meaningful information from digital images; for such purposes, techniques from image processing, computer vision, and machine learning are used. The range of such fields can be as simple as reading bar codes, as complex as reading car license plates, or even more complicated, for example, analyzing facial expressions and emotions.

Am especially interesting branch is document image analyzing, which targets problems such as handwriting recognition, page layout analysis, writer identification, and verification, check processing, and historical document processing, to extract useful information from document images as humans can do.

This Special Issue aims to collect the results of leading researchers and scientists in the field, to contribute their articles, and to be an assessment tool for people who are new to the world of document mathematical imaging and image processing.

This Special Issue intends to cover the following topics, but is not limited to them:

  • Image Analysis
  • Computer Vision
  • Document Image Analysis
  • Image\Document Understanding
  • Document Processing
  • Camera-based Document Processing
  • Document Databases and Digital Libraries
  • Mining Document Image Collections
  • Document Forensics
  • Historical Documents
  • Segmentation and Restoration
  • Performance Evaluation
  • Camera and Scene Text Understanding
  • Machine Learning for Document Analysis
  • Human–Document Interaction
  • Novel Applications

Indeed, any work concerning the use of document/image processing, as well the development of new application procedures, may fall within the scope of this Special Issue. Of course, papers must present novel results or the advancement of previously published data.

Dr. Raid Saabni
Guest Editor

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Keywords

  • image processing
  • computer vision
  • pattern recognition
  • document image analysis
  • machine learning
  • deep learning
  • document image analysis
  • historical document images

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Published Papers (1 paper)

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Research

25 pages, 6721 KiB  
Article
3D22MX: Performance Subjective Evaluation of 3D/Stereoscopic Image Processing and Analysis
by Jesús Jaime Moreno Escobar, Erika Yolanda Aguilar del Villar, Oswaldo Morales Matamoros and Liliana Chanona Hernández
Mathematics 2023, 11(1), 171; https://doi.org/10.3390/math11010171 - 29 Dec 2022
Viewed by 1657
Abstract
This work is divided into three parts: (i) a methodology developed for building a 3D/ stereoscopic database, called 3D22MX, (ii) a software tool designed for degradation of 3D/stereoscopic images, and (iii) a psychophysical experiment carried out for a specific type [...] Read more.
This work is divided into three parts: (i) a methodology developed for building a 3D/ stereoscopic database, called 3D22MX, (ii) a software tool designed for degradation of 3D/stereoscopic images, and (iii) a psychophysical experiment carried out for a specific type of noise. The novelty of this work is to integrate these three parts precisely to provide not only professionals who design algorithms to estimate three-dimensional image quality but also those who wish to generate new image databases. For the development of the 3D/stereoscopic database, 15 indoor images and 5 outdoor ones were spatial-calibrated and lighted for different types of scenarios. Criteria calibration is different for indoor images with respect to outdoor images. The software tool to degrade 3D/stereoscopic images is designed from MatLab programming language since images captured in the first part are calculated for achieving several image degradation. Our program has ten different types of noises for degradation, such as white Gauss impulse, localvar, spatial correlation, salt & pepper, speckle, blur, contrast, jpeg, and j2k. Due to each type of noise containing up to five levels of degradation, in this proposal, a database of 20 images is required to design a tool for degrading and generating three-dimensional images ranging from all types of noise to yield psychophysical. Finally, there are applied specific criteria to carry out some psychophysical experiments with 3D/stereoscopic images. Moreover, we analyzed the methodology used to qualify and apply images to the j2k noise, explaining every degradation level for this noise. Full article
(This article belongs to the Special Issue Mathematical Imaging: Theory and Applications)
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