Design And Implementation Of Image Detection System Based On Camera And Image Features

With the rapid development of the Internet,digital images have been becoming one of the important carriers of information and are widely spread on the Internet;the rise of various image editing software has made image editing easily,and the original content in digital images can be rewritten.It provides great convenience for the dissemination of information,but also brings great challenges to the fields of judicial evidence collection and criminal investigation.Whether in the field of scientific research or judicial forensics,false image detection is a very important and challenging task.For the problem of false image detection,this paper improves,optimizes and combines the image traceability detection method based on dust characteristics,the image traceability detection method based on pattern noise and the traceability detection method based on image content,and designs it to use JavaWeb as the system Framed image detection system.The system has high detection accuracy of digital images,fast detection speed,and high stability.This paper implements the image detection system from two aspects: active detection technology and passive detection technology.Active detection technology is based on the relevant information of the source device of the digital image.It mainly includes the retrospective detection of unique information such as the pattern noise of the shooting device and the dust spots of the sensor;passive detection technology is to detect the image without the prior information of the shooting device.In the active detection method,this paper focuses on the image traceability detection method based on dust characteristics and the image traceability detection method based on pattern noise.After detailed analysis of the two mathematical models,the parameters of the algorithm are adjusted by experiment and optimization.In the passive detection method,this paper designs an image traceability detection method based on RGB histogram statistical features,and optimizes the dimensionality reduction of feature descriptors for the false image detection method based on RGB histogram statistical features.At the same time,this paper proposes a detection method based on image blocks.This method can not only shorten the detection time of the algorithm,but also locate the image tampering area accurately.Finally,this paper designs an image detection system based on JavaWeb through these algorithms,and realizes the functions of image source detection,copy paste detection and so on.Compared with the previous image detection systems,the detection system designed in this paper use optimized detection algorithms,and use technologies such as caching and multi-threading to improve the system detection efficiency and the accuracy of system detection.At the same time,the system is in user interaction and management Image files and other aspects have better convenience,It provides strong technical support for image management and inspection of media organizations such as graphic magazines and magazines.The end of this article describes in detail the construction of image detection system and the process of test verification.After verification,the image detection system designed in this paper has high accuracy in image source detection,and the detection consumes less time,which can achieve the effect of real-time detection.At the same time,the functions of image copy-paste detection and block-based image detection also have very good accuracy and real-time performance.