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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hailing Zhou Llewellyn, L. Lei Wei Creighton, D. Nahavandi, S. |
| Copyright Year | 2015 |
| Description | Author affiliation: Centre for Intell. Syst. Res., Deakin Univ., Melbourne, VIC, Australia (Hailing Zhou; Lei Wei; Creighton, D.; Nahavandi, S.) || Australian Inst. of Marine Sci., Townsville, QLD, Australia (Llewellyn, L.) |
| Abstract | Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive way via setting up a camera and seeking objects in images is more promising. In this paper, a novel technique of object detection in images is presented, which is applicable to generic objects. A robust background modelling algorithm is proposed to extract foregrounds and then blob features are introduced to classify foregrounds. Particular marine objects, box jellyfish and sea snake, are successfully detected in our work. Experiments conducted on image datasets collected by the Australian Institute of Marine Science (AIMS) demonstrate the effectiveness of the proposed technique. |
| Starting Page | 430 |
| Ending Page | 435 |
| File Size | 1215946 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479986972 |
| DOI | 10.1109/SMC.2015.86 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-09 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Image segmentation Image color analysis Animals Cameras Training Australia marine object Object detection object recognition jellyfish sea snake |
| Content Type | Text |
| Resource Type | Article |
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