Special Issue on Advances in Machine Vision, Image Processing, and Pattern Analysis, Part 1 GueSt edItorIAl PrefAce (original) (raw)

A lot of advancements have been made recently in the field of image processing and pattern analysis. This special issue of IJSDA aims to focus upon the latest developments in theory, methodologies and applications in the highly interdisciplinary research arena of machine vision, image processing and pattern analysis. The theme addresses mathematical, physical, architectural and computational aspects of machine vision, analysis, matching and recognition along with its subsequent connection with Human Vision System (HVS). Further, it is known that computational intelligence serves as a powerful tool to mimic and process human knowledge. The integration of artificial intelligence, soft computing and machine learning adds to various computational enhancements in machine vision and image processing. This special issue consists of the extended version of papers which were initially presented at the Third International Conference on Frontiers in Intelligent Computing: Theory and Applicatio...

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The vitality of pattern recognition and image analysis

2015

Not many decades ago, Pattern Recognition and Image Analysis (PR&IA) addressed with simple tasks applying shallow models. But things are changing, and quickly. Then, this highly dynamic discipline has been expanding greatly, also helped by the emergence of newer application such as in robotics, biometrics or multimedia systems. Just now, PR&IA tasks run the complete gamut: from preprogramed works to the stimulating challenge of getting computers to learn as they go. At their most formidable, PR&IA tasks require computers to look, interpret and report back. We are at a transition point where PR&AI are suddenly at the forefront. Progress has come about thanks in part to steady advance in the technologies needed to help machines understand visual data, including machine learning and data mining techniques. The papers included in this special issue provide a snapshot of image analysis and pattern recognition research today. They are the very best of the 6th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2013), held on 5-7 June, 2013 in Madeira, Portugal. IbPRIA 2013 attracted 181 papers from 34 different countries. After the reviewing process, 105 papers were accepted for presentation in the conference. A selection of the best scored and presented at the conference was invited to submit to this special issue a substantially extended and revised version of the conference paper and the resulting manuscripts were sent out for full review. The process, including required revisions, was in accordance with the standing editorial policy of Neurocomputing, resulting in the final versions of the ten papers accepted and appearing in this special issue.

Computational Intelligence in Multi-Feature Visual Pattern Recognition

Studies in Computational Intelligence, 2014

The series ''Studies in Computational Intelligence'' (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the worldwide distribution, which enable both wide and rapid dissemination of research output.

Image Processing in Artificial Intelligence

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2020

Machines can learn to elucidate images the same way our brains do and analyse those images much more thoroughly than we can. When applied to Image Processing, Artificial Intelligence (AI) can propel face recognition and security functionality in public places, detecting and recognizing intruders, objects, and patterns in live images and videos, etc. Image processing technology focuses on the development of data extraction methods applied to the statistical classification of visual imagery. In classical image processing systems, an image is pre-processed to remove noise (denoising), segmented to produce close object boundaries, analysed to extract a representative feature, and compared to the ideal object feature vectors by a classifier to decide the nearest object classification and its associated level. In this paper, we discuss about digital image processing and the role of AI in it.

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