6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Heuristic Analysis Model of Nitrided Layers’ Formation Consisting of the Image Processing and Analysis and Elements of Artificial Intelligence

      research-article
      1 , * , 2
      Materials
      MDPI
      image analysis, surface layer, gas nitriding, artificial intelligence

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The article presents a selected area of research and development concerning the methods of material analysis based on the automatic image recognition of the investigated metallographic sections. The objectives of the analyses of the materials for gas nitriding technology are described. The methods of the preparation of nitrided layers, the steps of the process and the construction and operation of devices for gas nitriding are given. We discuss the possibility of using the methods of digital images processing in the analysis of the materials, as well as their essential task groups: improving the quality of the images, segmentation, morphological transformations and image recognition. The developed analysis model of the nitrided layers formation, covering image processing and analysis techniques, as well as selected methods of artificial intelligence are presented. The model is divided into stages, which are formalized in order to better reproduce their actions. The validation of the presented method is performed. The advantages and limitations of the developed solution, as well as the possibilities of its practical use, are listed.

          Related collections

          Most cited references23

          • Record: found
          • Abstract: not found
          • Book: not found

          Fuzzy Logic with Engineering Applications

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Fast and accurate center of gravity defuzzification of fuzzy system outputs defined on trapezoidal fuzzy partitions

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              IRGS: image segmentation using edge penalties and region growing.

              This paper proposes an image segmentation method named iterative region growing using semantics (IRGS), which is characterized by two aspects. First, it uses graduated increased edge penalty (GIEP) functions within the traditional Markov random field (MRF) context model in formulating the objective functions. Second, IRGS uses a region growing technique in searching for the solutions to these objective functions. The proposed IRGS is an improvement over traditional MRF based approaches in that the edge strength information is utilized and a more stable estimation of model parameters is achieved. Moreover, the IRGS method provides the possibility of building a hierarchical representation of the image content, and allows various region features and even domain knowledge to be incorporated in the segmentation process. The algorithm has been successfully tested on several artificial images and synthetic aperture radar (SAR) images.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Materials (Basel)
                Materials (Basel)
                materials
                Materials
                MDPI
                1996-1944
                01 April 2016
                April 2016
                : 9
                : 4
                : 265
                Affiliations
                [1 ]Institute for Sustainable Technologies, National Research Institute, Pulaski Str. 6/10, 26-600 Radom, Poland
                [2 ]Industrial Research Institute for Automation and Measurements PIAP, Jerozolimskie 202, 02-486 Warsaw, Poland; nowicki@ 123456mchtr.pw.edu.pl
                Author notes
                [* ]Correspondence: tomasz.wojcicki@ 123456itee.radom.pl ; Tel.: +48-48-364-4241 (ext. 261); Fax: +48-48-364-4760
                Article
                materials-09-00265
                10.3390/ma9040265
                5502929
                89446e78-c7a3-4727-b764-b7d65777cb0a
                © 2016 by the authors;

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 01 September 2015
                : 29 March 2016
                Categories
                Article

                image analysis,surface layer,gas nitriding,artificial intelligence

                Comments

                Comment on this article