随着智能手机的普及应用和地理信息提取技术的发展,将智能手机拍摄的数码照片中包含有坐标信息的地物转换成地理信息数据成为可能。Exif是数码照片的元数据,在使用移动设备拍摄照片时,可将拍摄时用户的位置信息存储在Exif信息中。通过分...随着智能手机的普及应用和地理信息提取技术的发展,将智能手机拍摄的数码照片中包含有坐标信息的地物转换成地理信息数据成为可能。Exif是数码照片的元数据,在使用移动设备拍摄照片时,可将拍摄时用户的位置信息存储在Exif信息中。通过分析Exif的结构并提取地理位置信息,基于微信公众平台,结合ArcGIS API for JavaScript和腾讯地图API,设计出一套面向社会公众使用的地理信息数据采集工具,并在实地测试中得到了验证。该成果将为城市综合治理、自然资源调查监测方面提供重要的技术支撑。展开更多
Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchang...Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format （EXIF） information of image for images authen- tication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.展开更多
文摘随着智能手机的普及应用和地理信息提取技术的发展,将智能手机拍摄的数码照片中包含有坐标信息的地物转换成地理信息数据成为可能。Exif是数码照片的元数据,在使用移动设备拍摄照片时,可将拍摄时用户的位置信息存储在Exif信息中。通过分析Exif的结构并提取地理位置信息,基于微信公众平台,结合ArcGIS API for JavaScript和腾讯地图API,设计出一套面向社会公众使用的地理信息数据采集工具,并在实地测试中得到了验证。该成果将为城市综合治理、自然资源调查监测方面提供重要的技术支撑。
基金supported by the National Natural Science Foundation of China under Grant Nos.61370195and 11101048Beijing Natural Science Foundation under Grant No.4132060the National Cryptography Development Foundation of China under Grant No.MMJJ201201002
文摘Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format （EXIF） information of image for images authen- tication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.
