Research On The Key Technology Of Vegetable Greenhouse Monitoring Video Processing

With the development of agricultural economy in China,people turn to the demand of agricultural products from quantity to quality.In recent years,agricultural products quality and safety incidents occurred frequently.For people's health and good economic order of agricultural products markets,it is necessary to establish agricultural products' quality safety traceability systems.Monitoring of the greenhouse is an important part of the agricultural products traceability,It is effective to improve the quality safety of agricultural products by real-time monitoring of the production process of vegetable greenhouse and the useful information embedded in the video.There are a lot of redundant information in the surveillance video.Most effective information exists in the foreground of the video,so it is necessary to carry out the work of the background separation.At present,the application of the traditional motion detection algorithm in the complex scene is relatively low.Under the support of Tianjin Food Safety&Low Carbon Manufacturing Collaborative Innovation Center,an improved codebook model algorithm is proposed in this paper.Combined with BP neural network and compression algorithm,the application of moving target detection is extended.The main results of this paper include:1.Comparing the advantages and disadvantages of several traditional detection algorithms.Through the experimental verification,the selection of the code book model is improved,and it has better detection effect and can adapt to more complex scenes.2.The moving foreground of the code book model is further detected.By using the BP neural network to classify the foreground objects,the practical needs of the application are obtained.3.Using the video compression algorithm,the video has the potential of the emergence of the part and the prospect of different compression processing.To reduce the amount of video data in the same time as the guarantee of information.