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RISS 인기검색어
- 검색키워드
- 저자 : Algarni Abeer D. (검색결과 3 건)
- 무료
- 기관 내 무료
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Hao Shuhui,Huang Changcheng,Heidari Ali Asghar,Chen Huiling,Li Lingzhi,Algarni Abeer D.,Elmannai Hela,Xu Suling 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.2
If found and treated early, fast-growing skin cancers can dramatically prolong patients’ lives. Dermoscopy is a convenient and reliable tool during the fore-period detection stage of skin cancer, so the efficient processing of digital images of dermoscopy is particularly critical to improving the level of a skin cancer diagnosis. Notably, image segmentation is a part of image preprocessing and essential technical support in the process of image processing. In addition, multi-threshold image segmentation (MIS) technology is extensively used due to its straightforward and effective features. Many academics have coupled different meta-heuristic algorithms with MIS to raise image segmentation quality. Nonetheless, these meta-heuristic algorithms frequently enter local optima. Therefore, this paper suggests an improved salp swarm algorithm (ILSSA) method that combines iterative mapping and local escaping operator to address this drawback. Besides, this paper also proposes the ILSSA-based MIS approach, which is triumphantly utilized to segment dermoscopic images of skin cancer. This method uses two-dimensional (2D) Kapur’s entropy as the objective function and employs non-local means 2D histogram to represent the image information. Furthermore, an array of benchmark function test experiments demonstrated that ILSSA could alleviate the local optimal problem more effectively than other compared algorithms. Afterward, the skin cancer dermoscopy image segmentation experiment displayed that the proposed ILSSA-based MIS method obtained superior segmentation results than other MIS peers and was more adaptable at different thresholds.
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Abbass Mohammed Y.,Sadic Nevein,Ashiba Huda I.,Hassan Emad S.,El-Dolil Sami,Soliman Naglaa F.,Algarni Abeer D.,Alabdulkreem Eatedal A.,Algarni Fatimah,El-Banby Ghada M.,Abdel-Rahman Mohamed R.,Aldosar 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.5
Infrared (IR) image sequences are acquired with certain types of cameras. These cameras give the sequence of images according to the heat distribution. With time, some deterioration of the quality of the sequence occurs due the thermal noise eff ect generated in the camera. This thermal noise eff ect leads to some sort of non-uniformity in the obtained image sequence. Hence, it is necessary to perform some sort of non-uniformity correction in the video sequence according to the fi rst frame. This type of non-uniformity correction is scene-based. This paper introduces a scene-based non-uniformity correction technique that depends mainly on histogram matching. The noise eff ect on each frame in the sequence leads to some drift in the histogram of that frame. Hence, the proposed technique depends on the histogram matching concept to correct the histogram of each frame in the sequence based on the histogram of the fi rst frame that is free from the thermal noise eff ect. Diff erent image quality metrics including entropy, contrast, edge intensity, average gradient, and correlation with the fi rst frame are adopted to assess the quality of the obtained frames after adjustment. It is required in the frames to be corrected to reduce entropy, edge intensity and average gradient as these metrics are increased with the presence of thermal noise eff ect on all pixels represented as much details and unnecessary information. In addition, the contrast of the video sequences should be increased to determine objects in a better way. The correlation of the corrected frames with the fi rst one should be increased to reduce the noise eff ect. Simulation results reveal enhanced quality of the obtained video sequences after processing with the proposed technique.
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Qi Ailiang,Zhao Dong,Yu Fanhua,Liu Guangjie,Heidari Ali Asghar,Chen Huiling,Algarni Abeer D.,Elmannai Hela,Gui Wenyong 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.6
The slime mould algorithm (SMA) has become a classical algorithm applied in many fields since it was presented. Nevertheless, when faced with complex tasks, the algorithm converges slowly and tends to fall into the local optimum. So, there is still room for improvement in the performance of SMA. This work proposes a novel SMA variant (SDSMA), combining the adaptive Lévy diversity mechanism and directional crossover mechanism. Firstly, the adaptive Lévy diversity mechanism can improve population diversity. Then, the directional crossover mechanism can enhance the balance of exploration and exploitation, thus helping SDSMA to increase the convergence speed and accuracy. SDSMA is compared with SMA variants, original algorithms, improved algorithms, improved-SMAs, and others on the benchmark function set to verify its performance. Meanwhile, the Wilcoxon signed-rank test, the Friedman test, and other analytical methods are considered to analyze the experimental results. The analysis results show that SDSMA with two strategies significantly improves the performance of SMA. Meanwhile, the computational cost of SDSMA is smaller than that of SMA on benchmark function. Finally, the proposed algorithm is applied to three real-world engineering design problems. The experiments prove that SDSMA is an effective aid tool for computationally complex practical tasks.
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