Detecting method and detecting device for survival of chick embryo

Abstract

The invention discloses a detecting method and a detecting device for survival of a chick embryo and belongs to the field of image processing. The method comprises the following steps: acquiring a chick embryo image; extracting R, G and B values of all pixel points in the chick embryo image, and carrying out blood vessel and air chamber detection on the basis of the R, G and B values to obtain a series of characteristic values for characterizing the color of the chick embryo image, the blood vessels and the air chamber; classifying the series of characteristic values by using a pretrained classifier to obtain a detection result for the survival of the chick embryo. According to the detecting method and the detecting device disclosed by the invention, treatment speed, accuracy and robustness of survival detection of the chick embryo can be improved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method and device for detecting viability of chicken embryos. Background technique [0002] At present, most domestic bird flu vaccines, animal flu vaccines (such as swine flu, canine flu, etc.) and some human vaccines (such as influenza A, hepatitis B vaccine, etc.) are produced by the "chicken embryo method", that is, the way of cultivating viruses in embryonated eggs . Chicken embryos are the carrier of virus culture. Chicken embryos are strictly screened to consider whether they are fertilized, whether they are polluted, the number of days, and their size. After a period of cultivation, the virus is extracted from chicken embryos, and the vaccination vaccine is produced after inactivation and other processes. [0003] The survival of chicken embryos and eggs is closely related to the quality, safety and cost of vaccine production. The detection of the survival of chicken e...

AI Technical Summary

Problems solved by technology

Although the above-mentioned chicken embryo viability detection method has achieved good detection results, it still has many defects.

First of all, because the judgment basis of this method needs to deal with a large number of digital characteristic parameters, it will greatly reduce the computer processing speed

Secondly, this method also requires a large amount of data storage, resulting in a low detection speed of the entire system, which cannot meet the real-time detection speed requirements of the industrial production line

In addition, this detection method is only limited to white-shelled eggs, and the detection effect on red-shelled eggs is not ideal.

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