Multichannel Saliency Detection Based on Visual Bionics
Inspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was us...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2020/8886923 |
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| _version_ | 1832560071344652288 |
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| author | Lidan Cheng Tianyi Li Shijia Zha Wei Wei Jihua Gu |
| author_facet | Lidan Cheng Tianyi Li Shijia Zha Wei Wei Jihua Gu |
| author_sort | Lidan Cheng |
| collection | DOAJ |
| description | Inspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was used to segment and cluster the RGBD image. Secondly, the depth saliency of the image region was obtained according to the anisotropic center-surround difference method. Then, the global feature saliency of RGB image was calculated according to the colour perception rule of human vision. The obtained multichannel saliency maps were weighted and fused based on information entropy to highlighting the target area and get the final detection results. The proposed method works within a complexity of O(N), and the experimental results show that our algorithm based on visual bionics effectively suppress the interference of similar or complex background and has high accuracy and stability. |
| format | Article |
| id | doaj-art-e1b7742c6b1545faa31cc8a68c9eae2e |
| institution | Kabale University |
| issn | 1176-2322 1754-2103 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-e1b7742c6b1545faa31cc8a68c9eae2e2025-02-03T01:28:33ZengWileyApplied Bionics and Biomechanics1176-23221754-21032020-01-01202010.1155/2020/88869238886923Multichannel Saliency Detection Based on Visual BionicsLidan Cheng0Tianyi Li1Shijia Zha2Wei Wei3Jihua Gu4College of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province 215000, ChinaInspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was used to segment and cluster the RGBD image. Secondly, the depth saliency of the image region was obtained according to the anisotropic center-surround difference method. Then, the global feature saliency of RGB image was calculated according to the colour perception rule of human vision. The obtained multichannel saliency maps were weighted and fused based on information entropy to highlighting the target area and get the final detection results. The proposed method works within a complexity of O(N), and the experimental results show that our algorithm based on visual bionics effectively suppress the interference of similar or complex background and has high accuracy and stability.http://dx.doi.org/10.1155/2020/8886923 |
| spellingShingle | Lidan Cheng Tianyi Li Shijia Zha Wei Wei Jihua Gu Multichannel Saliency Detection Based on Visual Bionics Applied Bionics and Biomechanics |
| title | Multichannel Saliency Detection Based on Visual Bionics |
| title_full | Multichannel Saliency Detection Based on Visual Bionics |
| title_fullStr | Multichannel Saliency Detection Based on Visual Bionics |
| title_full_unstemmed | Multichannel Saliency Detection Based on Visual Bionics |
| title_short | Multichannel Saliency Detection Based on Visual Bionics |
| title_sort | multichannel saliency detection based on visual bionics |
| url | http://dx.doi.org/10.1155/2020/8886923 |
| work_keys_str_mv | AT lidancheng multichannelsaliencydetectionbasedonvisualbionics AT tianyili multichannelsaliencydetectionbasedonvisualbionics AT shijiazha multichannelsaliencydetectionbasedonvisualbionics AT weiwei multichannelsaliencydetectionbasedonvisualbionics AT jihuagu multichannelsaliencydetectionbasedonvisualbionics |