Fast Pig Detection with a Top-View Camera under Various Illumination Conditions
The fast detection of pigs is a crucial aspect for a surveillance environment intended for the ultimate purpose of the 24 h tracking of individual pigs. Particularly, in a realistic pig farm environment, one should consider various illumination conditions such as sunlight, but such consideration has...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-02-01
|
| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/11/2/266 |
| _version_ | 1811264099217047552 |
|---|---|
| author | Jaewon Sa Younchang Choi Hanhaesol Lee Yongwha Chung Daihee Park Jinho Cho |
| author_facet | Jaewon Sa Younchang Choi Hanhaesol Lee Yongwha Chung Daihee Park Jinho Cho |
| author_sort | Jaewon Sa |
| collection | DOAJ |
| description | The fast detection of pigs is a crucial aspect for a surveillance environment intended for the ultimate purpose of the 24 h tracking of individual pigs. Particularly, in a realistic pig farm environment, one should consider various illumination conditions such as sunlight, but such consideration has not been reported yet. We propose a fast method to detect pigs under various illumination conditions by exploiting the complementary information from depth and infrared images. By applying spatiotemporal interpolation, we first remove the noises caused by sunlight. Then, we carefully analyze the characteristics of both the depth and infrared information and detect pigs using only simple image processing techniques. Rather than exploiting highly time-consuming techniques, such as frequency-, optimization-, or deep learning-based detections, our image processing-based method can guarantee a fast execution time for the final goal, i.e., intelligent pig monitoring applications. In the experimental results, pigs could be detected effectively through the proposed method for both accuracy (i.e., 0.79) and execution time (i.e., 8.71 ms), even with various illumination conditions. |
| first_indexed | 2024-04-12T19:58:15Z |
| format | Article |
| id | doaj.art-bf4ca58a4a7f4bafb6c78ae005f7bf2c |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-12T19:58:15Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-bf4ca58a4a7f4bafb6c78ae005f7bf2c2022-12-22T03:18:37ZengMDPI AGSymmetry2073-89942019-02-0111226610.3390/sym11020266sym11020266Fast Pig Detection with a Top-View Camera under Various Illumination ConditionsJaewon Sa0Younchang Choi1Hanhaesol Lee2Yongwha Chung3Daihee Park4Jinho Cho5Department of Computer Convergence Software, Korea University, Sejong 30019, KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, KoreaDivision of Food and Animal Science, Chungbuk National University, Cheongju 28644, KoreaThe fast detection of pigs is a crucial aspect for a surveillance environment intended for the ultimate purpose of the 24 h tracking of individual pigs. Particularly, in a realistic pig farm environment, one should consider various illumination conditions such as sunlight, but such consideration has not been reported yet. We propose a fast method to detect pigs under various illumination conditions by exploiting the complementary information from depth and infrared images. By applying spatiotemporal interpolation, we first remove the noises caused by sunlight. Then, we carefully analyze the characteristics of both the depth and infrared information and detect pigs using only simple image processing techniques. Rather than exploiting highly time-consuming techniques, such as frequency-, optimization-, or deep learning-based detections, our image processing-based method can guarantee a fast execution time for the final goal, i.e., intelligent pig monitoring applications. In the experimental results, pigs could be detected effectively through the proposed method for both accuracy (i.e., 0.79) and execution time (i.e., 8.71 ms), even with various illumination conditions.https://www.mdpi.com/2073-8994/11/2/266agriculture ITcomputer visionpig detectiondepth informationinfrared information |
| spellingShingle | Jaewon Sa Younchang Choi Hanhaesol Lee Yongwha Chung Daihee Park Jinho Cho Fast Pig Detection with a Top-View Camera under Various Illumination Conditions Symmetry agriculture IT computer vision pig detection depth information infrared information |
| title | Fast Pig Detection with a Top-View Camera under Various Illumination Conditions |
| title_full | Fast Pig Detection with a Top-View Camera under Various Illumination Conditions |
| title_fullStr | Fast Pig Detection with a Top-View Camera under Various Illumination Conditions |
| title_full_unstemmed | Fast Pig Detection with a Top-View Camera under Various Illumination Conditions |
| title_short | Fast Pig Detection with a Top-View Camera under Various Illumination Conditions |
| title_sort | fast pig detection with a top view camera under various illumination conditions |
| topic | agriculture IT computer vision pig detection depth information infrared information |
| url | https://www.mdpi.com/2073-8994/11/2/266 |
| work_keys_str_mv | AT jaewonsa fastpigdetectionwithatopviewcameraundervariousilluminationconditions AT younchangchoi fastpigdetectionwithatopviewcameraundervariousilluminationconditions AT hanhaesollee fastpigdetectionwithatopviewcameraundervariousilluminationconditions AT yongwhachung fastpigdetectionwithatopviewcameraundervariousilluminationconditions AT daiheepark fastpigdetectionwithatopviewcameraundervariousilluminationconditions AT jinhocho fastpigdetectionwithatopviewcameraundervariousilluminationconditions |