Large-scale farm sign abnormal bird detection system and detection method thereof

Abstract

The invention relates to a large-scale farm sign abnormal bird detection method, which comprises the following steps: pre-processing the collected thermographic images for data annotation, then adopting an instance-based segmentation general framework (Mask RCNN) target detection and instance separation method for feature extraction, pixel alignment, target positioning, classification and mask separation for thermal imaging images, by controlling the target detection number of a single image, improving the detection accuracy rate in each image. The method is an attempt in the field of target detection of current thermal imaging images, breaks the limitations brought by the traditional methods, and uses the superior performance of deep learning in image feature processing to improve the robustness and accuracy of a model. The feasibility of the deep learning method in the field of thermal imaging image detection is verified. At the same time, the method can also be extended to the livestock and other fields, thus improving the level of intelligence in the breeding industry in China.

Description

technical field [0001] The present invention generally relates to the fields of thermal imaging image processing, deep learning technology and target detection, and specifically relates to a detection system and detection method for poultry with abnormal signs in large-scale farms. Background technique [0002] At present, most of the domestic large-scale farms do not have a high level of intelligence, and manual participation is required to check whether there are individuals with abnormal signs in the chicken farm. However, manual inspection is very inefficient and time-consuming, and the general farms are relatively closed, the ventilation is not very good, and there is a lot of toxic gas. If people stay in the farm for a long time, it will have adverse effects on the body. . If the dead chicken is not found in a short period of time, the dead body will cultivate germs and spread continuously. The bird flu spreads rapidly and has a high infection rate, which will cause a...

AI Technical Summary

Problems solved by technology

But from the actual situation, some types of chickens do not have cockscombs, and the use of cockscombs to judge is somewhat accidental

In addition, the above algorithms need to manually extract features, the model adjustment is relatively large in different situations, the model is not robust to different poultry, and the image recognition effect will be greatly weakened in farms with insufficient light

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