|تعداد مشاهده مقاله||2,480,958|
|تعداد دریافت فایل اصل مقاله||1,748,408|
|Journal of Electrical and Computer Engineering Innovations (JECEI)|
|دوره 10، شماره 1، فروردین 2022، صفحه 243-258 اصل مقاله (1.51 M)|
|نوع مقاله: Review paper|
|شناسه دیجیتال (DOI): 10.22061/jecei.2021.8069.474|
|A. Ghanbari Talouki1؛ A. Koochari* 1؛ S. A. Edalatpanah2|
|1Department of Mechanic, Electrical and Computer, Science and Research Branch, Islamic Azad University, Tehran, Iran|
|2Department of Applied Mathematics, Ayandegan Institute of Higher Education, Tonekabon, Iran|
|تاریخ دریافت: 22 خرداد 1400، تاریخ بازنگری: 20 شهریور 1400، تاریخ پذیرش: 27 مهر 1400|
|Background and Objectives: Images and videos play significant roles in our lives. Moreover, there are considerable improvements in computer data collection systems; therefore, anyone is able to acquire much many images or videos, whereas he/she cannot process them manually. Images and videos became attractive since depicting and digital processing of these kinds of data became possible. Since indeterminacy surrounded the world, including images and videos of that; imprecision is needed to interpret this world.|
Methods: Neutosophic logic, which is from philosophy and is also included of logic, set theory and probability/statistics, is able to depict this imprecision. As a result, advanced image processing can be defined by translation of image processing into neutrosophic domain. In this paper, first of all, a general introduction about image/video processing (segmentation, noise reduction and image retrieval) and uncertainty is stated. Then, definitions of fuzzy sets, intuitionistic fuzzy sets and neutrosophic sets are expressed. In the following, applications of neutrosophic domain in image and video processing such as segmentation, noise reduction and image retrieval are introduced.
Results: Although, neutrosophic is used for image restoration and segmentation; input images are usually medical images or gray level natural images. The remarkable point is that there are few researches that focuse on image restoration or segmentation using neutrosophic and consider color images. Therefore, color image restoration and segmentation in neutrosophic environment is novel to be done.
Conclusion: Neutrosophic usage in image retrieval brings out an improvement in average recall and precision measure compared to earlier methods. Considering different textures and shapes can extend usages of neutrosophic space in image retrieval applications.
|neutrosophhic؛ image processing؛ segmentation؛ noise reduction؛ image retrieval|
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