Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Lahbib Khrissi"'
Autor:
Mohammed Es-sabry, Nabil El Akkad, Lahbib Khrissi, Khalid Satori, Walid El-Shafai, Torki Altameem, Rajkumar Singh Rathore
Publikováno v:
Egyptian Informatics Journal, Vol 25, Iss , Pp 100449- (2024)
In this study, we introduce a refined approach to encrypting 32-bit color images, leveraging the potential of four 1D chaotic maps – the Logistic map, Tent map, Chebyshev map, and Sine map. These chaotic maps intricately populate the four matrices
Externí odkaz:
https://doaj.org/article/850a2dd31d0f45c9bd8ddbceb05ca642
Publikováno v:
Journal of Engineering and Applied Science, Vol 70, Iss 1, Pp 1-20 (2023)
Abstract In the present study, we aim to propose an effective and robust ensemble-learning approach with stacked generalization for image segmentation. Initially, the input images are processed for feature extraction and edge detection using the Gabo
Externí odkaz:
https://doaj.org/article/fad3aacc36a44e9aadc3b0c5986d1ed4
Publikováno v:
International Journal of Computing. :159-168
Image segmentation is a fundamental and important step in many computer vision applications. One of the most widely used image segmentation techniques is clustering. It is a process of segmenting the intensities of a non-homogeneous image into homoge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b35517cdc49d57861c77d42a8c2e4ee
https://doi.org/10.47839/ijc.21.2.2584
https://doi.org/10.47839/ijc.21.2.2584
Publikováno v:
Evolutionary Intelligence. 15:669-682
This article presents a new image segmentation approach based on the principle of clustering optimized by the meta-heuristic algorithm namely: SCA (Algorithm Sinus Cosine). This algorithm uses a mathematical model based on trigonometric functions to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0154ad4ddbceaf4e6d1a25aac4093399
https://doi.org/10.1007/s12065-020-00544-z
https://doi.org/10.1007/s12065-020-00544-z
Publikováno v:
Digital Technologies and Applications ISBN: 9783030738815
Segmentation is the heart of an automatic image analysis system. There are several segmentation techniques. The contour segmentation approach aims to separate regions of different gray levels and relatively homogeneous. The region segmentation approa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42d8ed0b433d404ee36f4bd73a36cedf
https://doi.org/10.1007/978-3-030-73882-2_81
https://doi.org/10.1007/978-3-030-73882-2_81
Publikováno v:
International Journal of Advanced Computer Science and Applications. 12
Clustering is a predominant technique used in image segmentation due to its simple, easy and efficient approach. It is very important for the analysis, extraction and interpretation of images; which makes it used in multiple applications and in vario
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b705e4cfe8f75c1afdfddcbbfe38311
https://doi.org/10.14569/ijacsa.2021.0120647
https://doi.org/10.14569/ijacsa.2021.0120647
Publikováno v:
2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS).
Image segmentation is the most important operation in the image processing system because it is located at the articulation between image processing and analysis. The advantage of segmentation is to partition an image into several homogeneous regions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::169ed0255bd6840d90eb339201fa242c
https://doi.org/10.1109/icds50568.2020.9268754
https://doi.org/10.1109/icds50568.2020.9268754
Publikováno v:
2019 7th Mediterranean Congress of Telecommunications (CMT).
Image segmentation is an important step in any image analysis process. In the literature, there are two dual approaches. The contour segmentation approach consists in locating the object boundaries and the segmentation approach by region consists in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e17b939895fbd33a509427c97b92235f
https://doi.org/10.1109/cmt.2019.8931358
https://doi.org/10.1109/cmt.2019.8931358