Adaptive shadow detection using global texture and sampling deduction
An adaptive shadow detection algorithm is proposed to eliminate interference on object detection from the shadow. The algorithm uses three components in YUV colour space to identify shadow pixels from the candidate foreground. An adaptive threshold estimator is designed to improve shadow detection a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2012.0106 |
| _version_ | 1797685252201644032 |
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| author | Ke Jiang Ai‐hua Li Zhi‐gao Cui Tao Wang Yan‐zhao Su |
| author_facet | Ke Jiang Ai‐hua Li Zhi‐gao Cui Tao Wang Yan‐zhao Su |
| author_sort | Ke Jiang |
| collection | DOAJ |
| description | An adaptive shadow detection algorithm is proposed to eliminate interference on object detection from the shadow. The algorithm uses three components in YUV colour space to identify shadow pixels from the candidate foreground. An adaptive threshold estimator is designed to improve shadow detection accuracy and adaptive capacity in various lighting conditions. This estimator uses edge detection method to obtain global texture, as well statistical calculations to obtain the thresholds. Algorithm has the characteristic of low complexity and little restraint; hence it is suitable for real time‐moving shadow detection in various lighting conditions. Experiment results show that this algorithm can obtain a high detection accuracy and the time‐assume is greatly shortened compared with other algorithms with similar accuracy. |
| first_indexed | 2024-03-12T00:41:28Z |
| format | Article |
| id | doaj.art-a9778ab556034f8c85edb20a460dae25 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:41:28Z |
| publishDate | 2013-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-a9778ab556034f8c85edb20a460dae252023-09-15T07:06:43ZengWileyIET Computer Vision1751-96321751-96402013-04-017211512210.1049/iet-cvi.2012.0106Adaptive shadow detection using global texture and sampling deductionKe Jiang0Ai‐hua Li1Zhi‐gao Cui2Tao Wang3Yan‐zhao Su4502 FacultyXi'an Institute of High TechnologyXi'anShaan XiPeople's Republic of China502 FacultyXi'an Institute of High TechnologyXi'anShaan XiPeople's Republic of China502 FacultyXi'an Institute of High TechnologyXi'anShaan XiPeople's Republic of China502 FacultyXi'an Institute of High TechnologyXi'anShaan XiPeople's Republic of China502 FacultyXi'an Institute of High TechnologyXi'anShaan XiPeople's Republic of ChinaAn adaptive shadow detection algorithm is proposed to eliminate interference on object detection from the shadow. The algorithm uses three components in YUV colour space to identify shadow pixels from the candidate foreground. An adaptive threshold estimator is designed to improve shadow detection accuracy and adaptive capacity in various lighting conditions. This estimator uses edge detection method to obtain global texture, as well statistical calculations to obtain the thresholds. Algorithm has the characteristic of low complexity and little restraint; hence it is suitable for real time‐moving shadow detection in various lighting conditions. Experiment results show that this algorithm can obtain a high detection accuracy and the time‐assume is greatly shortened compared with other algorithms with similar accuracy.https://doi.org/10.1049/iet-cvi.2012.0106high detection accuracyreal time-moving shadow detectionstatistical calculationsedge detection methodlighting conditionsadaptive capacity |
| spellingShingle | Ke Jiang Ai‐hua Li Zhi‐gao Cui Tao Wang Yan‐zhao Su Adaptive shadow detection using global texture and sampling deduction IET Computer Vision high detection accuracy real time-moving shadow detection statistical calculations edge detection method lighting conditions adaptive capacity |
| title | Adaptive shadow detection using global texture and sampling deduction |
| title_full | Adaptive shadow detection using global texture and sampling deduction |
| title_fullStr | Adaptive shadow detection using global texture and sampling deduction |
| title_full_unstemmed | Adaptive shadow detection using global texture and sampling deduction |
| title_short | Adaptive shadow detection using global texture and sampling deduction |
| title_sort | adaptive shadow detection using global texture and sampling deduction |
| topic | high detection accuracy real time-moving shadow detection statistical calculations edge detection method lighting conditions adaptive capacity |
| url | https://doi.org/10.1049/iet-cvi.2012.0106 |
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