| Detection of small-sized insect pest in greenhouses based on multifractal analysis | |
Li Y(李岩) ; Xia, Chunlei; Lee, Jangmyung
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| Department | 水下机器人研究室 |
| Source Publication | Optik
 |
| ISSN | 0030-4026 |
| 2015 | |
| Volume | 126Issue:19Pages:2138-2143 |
| Indexed By | SCI ; EI |
| EI Accession number | 20152700989024 |
| WOS ID | WOS:000364604200080 |
| Contribution Rank | 1 |
| Funding Organization | National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIP) (grant no. NRF-2013R1A1A2021174). |
| Keyword | Multifractal Analysis Robot Vision Image Processing Pest Detection Small-size Pest |
| Abstract | A new application of multifractal analysis for the detection of small-sized pests (e.g., whitefly) from leaf surface images in situ is proposed in this paper. Multifractal analysis was adopted for segmentation of whitefly images based on the local singularity and global image characters with the regional minima selection strategy. According to the multifractal dimension, the candidate blobs of whiteflies were initially defined from the leaf image. The regional minima were utilized for feature extraction of candidate whitefly image areas and the performance was compared to that of the fixed threshold. Subsequently, most false alarms from leaf veins were decreased by consideration of the size and shape of the whiteflies. Experiments were conducted with field images in a greenhouse. Detection results were compared with other adaptive segmentation algorithms. Values of F measuring precision and recall scores were higher for the proposed multifractal analysis (88.6%) than for conventional methods such as Watershed (60.2%) and Efficient Graph-based Image Segmentation (EGBIS; 42.8%). The true-positive rate of multifractal analysis was 86.9% and the false-positive rate was at the minimum level of 8.2%. Overall, the detection of small-sized pests is most feasible with the proposed multifractal analysis under greenhouse conditions. |
| Language | 英语 |
| WOS Headings | Science & Technology ; Physical Sciences |
| WOS Subject | Optics |
| WOS Keyword | IMAGE SEGMENTATION ; MACHINE VISION ; MANAGEMENT ; EXTRACTION ; ALGORITHM ; CROPS ; GRAIN |
| WOS Research Area | Optics |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.sia.cn/handle/173321/16465 |
| Collection | 水下机器人研究室 |
| Corresponding Author | Lee, Jangmyung |
| Affiliation | 1.Department of Electrical Engineering, Pusan National University, Busan, Korea, Republic of 2.SPENALO Robot Technology Research Center, Pusan National University, Busan, Korea, Republic of 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China |
| Recommended Citation GB/T 7714 | Li Y,Xia, Chunlei,Lee, Jangmyung. Detection of small-sized insect pest in greenhouses based on multifractal analysis[J]. Optik,2015,126(19):2138-2143. |
| APA | Li Y,Xia, Chunlei,&Lee, Jangmyung.(2015).Detection of small-sized insect pest in greenhouses based on multifractal analysis.Optik,126(19),2138-2143. |
| MLA | Li Y,et al."Detection of small-sized insect pest in greenhouses based on multifractal analysis".Optik 126.19(2015):2138-2143. |
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| File Name/Size | DocType | Version | Access | License | ||
| Detection of small-s（1167KB） | 期刊论文 | 出版稿 | 开放获取 | ODC PDDL | View Application Full Text | |
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