Increasingly advanced image processing technology has made digital image editing easier and easier.With image processing software at one’s fingertips,one can easily alter the content of an image,and the altered image...Increasingly advanced image processing technology has made digital image editing easier and easier.With image processing software at one’s fingertips,one can easily alter the content of an image,and the altered image is so realistic that it is illegible to the naked eye.These tampered images have posed a serious threat to personal privacy,social order,and national security.Therefore,detecting and locating tampered areas in images has important practical significance,and has become an important research topic in the field of multimedia information security.In recent years,deep learning technology has been widely used in image tampering localization,and the achieved performance has significantly surpassed traditional tampering forensics methods.This paper mainly sorts out the relevant knowledge and latest methods in the field of image tampering detection based on deep learning.According to the two types of tampering detection based on deep learning,the detection tasks of the method are detailed separately,and the problems and future prospects in this field are discussed.It is quite different from the existing work:(1)This paper mainly focuses on the problem of image tampering detection,so it does not elaborate on various forensic methods.(2)This paper focuses on the detectionmethod of image tampering based on deep learning.(3)This paper is driven by the needs of tampering targets,so it pays more attention to sorting out methods for different tampering detection tasks.展开更多
A high-precision automatic state monitoring and abnormity alarm technique is proposed to solve the process improvement issues of fiber-optic coil winding and splicing. Industrial cameras are used to capture optical an...A high-precision automatic state monitoring and abnormity alarm technique is proposed to solve the process improvement issues of fiber-optic coil winding and splicing. Industrial cameras are used to capture optical and hot images during the assembly of optical components of a fiber-optic gyroscope. A line and contour analysis technique is used to detect abnormal winding. By analyzing the intensity distribution of transmitted light, the graph cut model and multivariate Gaussian mixture model are used to detect and segment the splicing defects. The practical applications indicate the correctness and accuracy of our vision-based technique.展开更多
基金supported by Key Projects of Innovation and Entrepreneurship Training Program for College Students in Jiangsu Province of China(202210300028Z).
文摘Increasingly advanced image processing technology has made digital image editing easier and easier.With image processing software at one’s fingertips,one can easily alter the content of an image,and the altered image is so realistic that it is illegible to the naked eye.These tampered images have posed a serious threat to personal privacy,social order,and national security.Therefore,detecting and locating tampered areas in images has important practical significance,and has become an important research topic in the field of multimedia information security.In recent years,deep learning technology has been widely used in image tampering localization,and the achieved performance has significantly surpassed traditional tampering forensics methods.This paper mainly sorts out the relevant knowledge and latest methods in the field of image tampering detection based on deep learning.According to the two types of tampering detection based on deep learning,the detection tasks of the method are detailed separately,and the problems and future prospects in this field are discussed.It is quite different from the existing work:(1)This paper mainly focuses on the problem of image tampering detection,so it does not elaborate on various forensic methods.(2)This paper focuses on the detectionmethod of image tampering based on deep learning.(3)This paper is driven by the needs of tampering targets,so it pays more attention to sorting out methods for different tampering detection tasks.
基金supported by the National "973" Program of China under Grant Nos.613186 and 2011CB711000
文摘A high-precision automatic state monitoring and abnormity alarm technique is proposed to solve the process improvement issues of fiber-optic coil winding and splicing. Industrial cameras are used to capture optical and hot images during the assembly of optical components of a fiber-optic gyroscope. A line and contour analysis technique is used to detect abnormal winding. By analyzing the intensity distribution of transmitted light, the graph cut model and multivariate Gaussian mixture model are used to detect and segment the splicing defects. The practical applications indicate the correctness and accuracy of our vision-based technique.
