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Salient object detection method based on object integrity enhancement guided by edge information.

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Title: Salient object detection method based on object integrity enhancement guided by edge information.
Authors: QIU, Haoqing1,2, GE, Hongwei1,2 ghw8601@163.com, LI, Ting2
Source: Journal of Measurement Science & Instrumentation. Jun2026, Vol. 17 Issue 2, p195-207. 13p.
Subjects: Feature extraction, Object recognition (Computer vision), Signal convolution
Abstract: In the saliency object detection task, a salient object detection method based on object integrity enhancement guided edge information is proposed to address the problems of blurred edges and object incompleteness in recognition results. Firstly, the diversity feature extraction module was proposed to capture the features of complex and variable salient objects through various convolutional operations, thereby enriching the feature representation of the model. Then, the object integrity enhancement module was designed to process the initial fused multi-level features in parallel, and the integrity information of salient objects was further enhanced by exploring spatial and channel branches. Finally, the edge feature enhancement module was employed to use the deep edge prediction features to guide the feature map to pay more attention to the foreground and background region and edge information, and to improve the model's edge perception capability. Experiments on four public datasets, such as ECSSD and DUTS-TE, showed that the proposed algorithm achieved higher detection accuracy than other advanced algorithms in several metrics, such as S-measure and F-measure on DUTS-TE dataset were 0.859 and 0.895, respectively. The proposed algorithm demonstrated superior capability in the perception and refinement of salient object boundaries, further enhancing its robustness in complex scenes. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Measurement Science & Instrumentation is the property of Journal of Measurement Science & Instrumentation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Measurement+Science+%26+Instrumentation%22">Journal of Measurement Science & Instrumentation</searchLink>. Jun2026, Vol. 17 Issue 2, p195-207. 13p.
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  Data: In the saliency object detection task, a salient object detection method based on object integrity enhancement guided edge information is proposed to address the problems of blurred edges and object incompleteness in recognition results. Firstly, the diversity feature extraction module was proposed to capture the features of complex and variable salient objects through various convolutional operations, thereby enriching the feature representation of the model. Then, the object integrity enhancement module was designed to process the initial fused multi-level features in parallel, and the integrity information of salient objects was further enhanced by exploring spatial and channel branches. Finally, the edge feature enhancement module was employed to use the deep edge prediction features to guide the feature map to pay more attention to the foreground and background region and edge information, and to improve the model's edge perception capability. Experiments on four public datasets, such as ECSSD and DUTS-TE, showed that the proposed algorithm achieved higher detection accuracy than other advanced algorithms in several metrics, such as S-measure and F-measure on DUTS-TE dataset were 0.859 and 0.895, respectively. The proposed algorithm demonstrated superior capability in the perception and refinement of salient object boundaries, further enhancing its robustness in complex scenes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Measurement Science & Instrumentation is the property of Journal of Measurement Science & Instrumentation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.62756/jmsi.1674-8042.2026017
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      – Code: eng
        Text: English
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        PageCount: 13
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      – SubjectFull: Feature extraction
        Type: general
      – SubjectFull: Object recognition (Computer vision)
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      – SubjectFull: Signal convolution
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      – TitleFull: Salient object detection method based on object integrity enhancement guided by edge information.
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              Text: Jun2026
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              Y: 2026
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