Identification of manipulation in digital images through hybrid block-based and key points algorithm
| Autor | Mohammad Hossein Tirnaz - Azam Bastan fard |
| Cargo | Islamic Azad university, Faculty of Mechatronics Science and Research Branch of Alborz, Karaj, Iran - Islamic Azad University, Department of computer engineering Science and Research Branch of Alborz, Karaj, Iran |
| Páginas | 78-92 |
QUID Nº28, pp. 78-92, enero-junio de 2017, ISSN: 1692-343X, Medellín -Colombia
IDENTIFICATION OF MANIPULATION IN DIGITAL IMAGES THROUGH HYBRID BLOCK-B ASED
AND KEY POINTS ALGORITHM
(Recibido el 16-01-2017. Aprobado el 11-04-2017)
MSc Mohammad Hossein Tirnaz
Islamic Azad university, Fa culty of Mechatronics
Science and Research Bra nch of Alborz, Kara j, Iran
Research@QIAU.ac.ir
PhD. Azam Bastan fard
Islamic Azad University, Depar tment of computer
engineering Science and Resear ch Branch of
Alborz, Kara j, Iran
Abstract: Nowadays, digital images in many legal centers are considered as a source of information and request to
determine the authenticity of an image has increased d ramatically. In this paper, an efficient algorithm to check and
identify manipulation in which a combination of block-based methods and key points for the extraction of forged
parts has been implemented. In the proposed algorithm, the input image is taken at First. After compliance with the
test target which is b ased on database, it is recognized that whether the image has been manipulated or not. In case
of observing a positive result, it is concluded that that forgery has been made. First, the input image is divided into
irregular and non-overlapping blocks using simple clustering algorithm (SLIC)
1. Then, feature points as the
characteristics of the blocks are extracted using loca l binary method with several resolutions. Block attributes are
adapted with each other to identify Areas suspected of forgery. In the second stage, for more accurate diagnosis of
forging parts, characteristic points were replaced with small super -pixels as characteristic blocks and adjacent
Features of blocks are replaced with the characteristics of positional color which are similar to feature blocks to
produce consolidated areas. Finally, RANSAC2 algorithm on integrated areas is used to remove false matches.
Experimental results using a test database and forgery rotation methods, blurring, jpeg compression and etc., show
that the proposed algorithm in the field of detection of copy-transfer forgery has reached to 97 percent and has also
achieved recall rate of 98 percent.it has been improved 3 percent compared to other valid methods in terms of
recalling and precision. This algorithm can even identify rotation methods, blur and jpeg compression by calculation
which have less complexity.
Keywords: areas suspected of forgery, super pi xel, block features, extraction of forged areas, the characteristic
points, social networks
Citar, estilo APA: Bastan fard, A., & Hossein, M. (2017). IDENTIFICATION O F MANIPULATION IN DIGITAL IMAGES THROUGH HYBRID BLOCK-
BASED AND KEY POINTS ALGORITHM. Revista QUID (28), 78-92.
1 Simple Linear Iterative Clustering
2 random sample consensus
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