自适应图像压缩的水稻病害诊断平台

Diagnosis Platform of Rice Diseases of Self-adapting Image Compression

针对手机客户端上传图片缓慢、损耗数据流量、图像处理能力有限等不便于病害图像的实时、准确诊断这一问题,提出一种在客户端将病害图像进行自适应压缩处理确保其清晰度和低容量大小后再上传的方法,并基于移动端开发了水稻病害图像诊断平台。系统总体分为移动端和服务器端,并利用http网络通信层将二者相连。围绕客户端和服务端的设计与实现,详细阐述了实现过程中的一些重要方法,如自适应图像压缩法、异步耗时压缩操作、JSON数据交换等。测试结果表明,该系统可解决图像上传缓慢、损耗数据流量等问题,同时可实时、准确地识别出病害种类,并提供准确的诊断信息和防治方法,在功能和性能上满足了用户的需求。

Because of the mobile-client uploading pictures slowly and lossing flow and limited image processing,it is not convenient todiagnose the rice diseases image accurately in time. In view of this,we put forward a method that the disease image can be adjusted andcompressed to ensure its clarity and low capacity on the client before uploading,and develop a diagnosis platform for the rice diseases inmobile phone client. The system is divided into client and server,they are connected by HTTP network communication layer. Based onthe design and implementation of client and server,some methods in the implementation,such as self-adapting image compression,asynchronous time compression,JSON data exchange,are discussed in detail. The test shows that the system can solve the problems like slowimages loading and data loss,identify the types of diseases accurately in time,and provide accurate diagnostic information and preventionmethods,which can meet the needs of users in function and performance.