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基于機(jī)器視覺的疫苗制備中胚蛋成活性檢測
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Fertility Detection in Vaccine Preparation Based on Machine Vision
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    摘要:

    將機(jī)器視覺技術(shù)引入疫苗制備的胚蛋孵化中期成活性檢測環(huán)節(jié)中。針對(duì)其不可漏檢壞死胚蛋的特殊需求,,提出了首先以多尺度形態(tài)學(xué)濾波增強(qiáng)圖像,、檢測圖像谷帶特征,,然后以基于直方圖WFCM的局部自適應(yīng)二值化方法提取血絲,最后通過血絲數(shù)量來判定成活性的算法,。以150幅圖像進(jìn)行實(shí)驗(yàn),,實(shí)驗(yàn)結(jié)果顯示,本算法檢測速度快,、對(duì)胚蛋活性無影響,。判定正確率、漏判率和誤判率分別為99.33%,、0和0.67%,,可滿足疫苗制備的特殊需求。

    Abstract:

    Machine vision was introduced into the vaccine preparation to detect the fertility of middle-stage hatching egg by using the image processing. According to the special requirements that all the infertile eggs should be detected and the original embryos fertility in eggs should not be affected by the detection, the design of imaging system and the method of how to detect the fertility by using the images were proposed. Firstly, images were enhanced and the special quality of shade was detected by multi-scale morphological transformation; secondly, the main blood-vessels in the hatching egg images was extracted by using local adaptive segmentation based on histogram-based WFCM; finally, the fertility by counting the number of the blood-vessels was detected. The method was simulated with 150 images under the Matlab7.0 environment. The detection accuracy rate, undetected error rate and false detected rate were respectively 99.33%, 0% and 0.67%. The detection of a single egg is 0.21s on average. The results showed that the method was efficient, but not sensitive to noise, color of egg shell, nor to the other pollution on the eggshell. It is capable to improve the detection accuracy and efficiency by replacing manual detection in vaccine preparation.

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單寶明.基于機(jī)器視覺的疫苗制備中胚蛋成活性檢測[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2010,41(5):178-181. Fertility Detection in Vaccine Preparation Based on Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(5):178-181.

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