removal of non-informative frames for wireless capsule endoscopy video segmentation
文献类型：会议论文
| 作者 | Sun Zhe ; Li Baopu ; Zhou Ran ; Zheng Huimin ; Meng Max Q.-H |
| 出版日期 | 2012 |
| 会议名称 | 2012 IEEE International Conference on Automation and Logistics, ICAL 2012 |
| 会议日期 | August 15, 2012 - August 17, 2012 |
| 会议地点 | Zhengzhou, China |
| 关键词 | Body fluids Discrete cosine transforms Endoscopy Removal |
| 页码 | 294-299 |
| 中文摘要 | Wireless capsule endoscopy (WCE) video segmentation plays an important part in WCE automatic diagnosis since it provides an effective method to help physicians and save time. In the automatic WCE video segmentation process, impurities frames with opaque digestive juice, food residues and excrement not only waste plentiful time, but also cause a lower accuracy of segmentation for its variation of color and pattern. The major impurities which have great affection for WCE video segmentation can be divided into two categories, gastric juice and bubbles. Thus, in this paper, a novel two-stage preprocessing approach is proposed to remove impurities frames in WCE videos. In the first stage, frames of gastric juice are eliminated by using local HS histogram features. In the second stage, a new approach is carried out to remove the bubbles frames in the WCE video, which combines Color Local Binary Patterns (CLBP) algorithm with Discrete Cosine Transform (DCT). K-Nearest Neighbor (KNN) classifier is used in both stages for its rapidity. Experiments demonstrate that the proposed scheme is an effective approach for removing non-informative frames in WCE video and the accuracies of each stage can reach as high as 99.31% and 97.54% respectively. © 2012 IEEE. |
| 英文摘要 | Wireless capsule endoscopy (WCE) video segmentation plays an important part in WCE automatic diagnosis since it provides an effective method to help physicians and save time. In the automatic WCE video segmentation process, impurities frames with opaque digestive juice, food residues and excrement not only waste plentiful time, but also cause a lower accuracy of segmentation for its variation of color and pattern. The major impurities which have great affection for WCE video segmentation can be divided into two categories, gastric juice and bubbles. Thus, in this paper, a novel two-stage preprocessing approach is proposed to remove impurities frames in WCE videos. In the first stage, frames of gastric juice are eliminated by using local HS histogram features. In the second stage, a new approach is carried out to remove the bubbles frames in the WCE video, which combines Color Local Binary Patterns (CLBP) algorithm with Discrete Cosine Transform (DCT). K-Nearest Neighbor (KNN) classifier is used in both stages for its rapidity. Experiments demonstrate that the proposed scheme is an effective approach for removing non-informative frames in WCE video and the accuracies of each stage can reach as high as 99.31% and 97.54% respectively. © 2012 IEEE. |
| 收录类别 | EI |
| 会议录 | IEEE International Conference on Automation and Logistics, ICAL
 |
| 语种 | 英语 |
| ISSN号 | 2161-8151 |
| ISBN号 | 9781467303620 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15841]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Sun Zhe,Li Baopu,Zhou Ran,et al. removal of non-informative frames for wireless capsule endoscopy video segmentation[C]. 见:2012 IEEE International Conference on Automation and Logistics, ICAL 2012. Zhengzhou, China. August 15, 2012 - August 17, 2012. |
入库方式： OAI收割
来源：软件研究所
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