Copy Move Forgery Detection Using Forensic Images

Digital images are open to several manipulations and dropped cost of compact cameras and mobile phones due to the robust image editing tools. Image credibility is therefore become doubtful, particularly where photos have power, for instance, news reports and insurance claims in a criminal court. Images forensic methods therefore measure the integrity of image by apply different highly technical methods established in literatures. The present work deals with copy move forgery images of Media Integration and Communication Center Forgery (MICC-F2000) dataset for detecting and revealing the areas that have been tampered portion in the image, the image is sectioned into non overlapping blocks using Simple liner iterative clustering (SLIC) method. Then, Scale invariant feature transform (SIFT) descriptor is applied on the grey of the handled image to gives distinctive key points that classified by K-Nearest neighbor to detect and localize the forged portion in the tempered image. The forgery detection results gave a performance percent of about 98%, which reflects the ability of the KNN classifier that cooperated with SIFT descriptor to detect the forged portions even if the forged area is rotated or scaled or both of them.

Pertautan Citra Tampak Atas dengan Metode Stereoskopik untuk Menghilangkan Distorsi Perspektif

Stitching citra with different object’s depth and disposed close to the camera willing caused panoramic citra with distortion perspective (caused double or disappear object) because the camera see in two dimension with large horizontal disparity by each camera. For solve that problem, stereoscopic method purpose to give depth perception of three dimension from two images with same background so information of depth by the object be able to get with intuitive way.This research presented system with ROI segmentation for any static objects, stitching for each objects and combine them become a panoramic image then shown in citra panoramic. SIFT descriptor used for detect and extract feature from the images. The result of this system successful presented combination for stitching by the static objects.