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基于圖像處理的生豬耳部顏色異常檢測(cè)技術(shù)
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國(guó)家國(guó)際科技合作專項(xiàng)(S2015ZR1137)


Pig Ear Abnormal Color Detection on Image Processing Techniques
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    摘要:

    為研究規(guī)?;i養(yǎng)殖場(chǎng)中藍(lán)耳病疫情預(yù)警監(jiān)測(cè)方法,,提出一種非接觸式耳部顏色自動(dòng)檢測(cè)方法,。該方法將生豬熱紅外圖像和可見光圖像相結(jié)合尋找最優(yōu)尺度因子,,確定可見光圖像中生豬耳根部特征區(qū)域,;采用主動(dòng)形狀模型方法,,選取34個(gè)生豬耳部輪廓特征點(diǎn),,并將搜索范圍限定在生豬頭部區(qū)域,,用以提取生豬耳部輪廓;將提取的耳部輪廓進(jìn)行顏色對(duì)比,,判斷該生豬是否患有藍(lán)耳病疫情,。結(jié)果表明,由于限定生豬頭部區(qū)域搜索范圍,,能快速準(zhǔn)確地提取生豬耳部輪廓,。對(duì)生豬耳部顏色檢測(cè)準(zhǔn)確率達(dá)到77%以上,。

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    In order to study blue ear epidemic early warning and monitoring method in large-scale pig farms, the non-contact ear automatic color detection method was proposed. Pig’s thermal infrared images and visual images were collected at the same time and the same viewing angle. Two pictures were used together to find the optimal scale factor of matching. By the optimal scale factor, pig ear root section can be found in visible image, and then the ear root central point can be confirmed. According to active shape model method, pig ear root central point was selected as the first feature point, the ear tip as 18th feature points, and both middle point of outlines as 9th and 26th feature points, and 34 pig ears outline feature points in all were selected by human-computer interaction. ASM search scope was defined in pig head region, thus pig ear outline could be extracted correctly. Then the extracted pig ear color was compared with the color of normal pig ears, the ear color detection accuracy could be above 77%, and it could be easily found whether there was the risk of blueear pig disease. The results showed that due to the limited search scope method, the pig ear contour could be extracted accurately, and it could be applied to auto ear color detection in swine house.

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周麗萍,陳達(dá),陳志,苑嚴(yán)偉,王麗麗,孫小文.基于圖像處理的生豬耳部顏色異常檢測(cè)技術(shù)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2017,48(4):166-172. ZHOU Liping, CHEN Da, CHEN Zhi, YUAN Yanwei, WANG Lili, SUN Xiaowen. Pig Ear Abnormal Color Detection on Image Processing Techniques[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(4):166-172.

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  • 收稿日期:2016-07-06
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  • 在線發(fā)布日期: 2017-04-10
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