This document provides a review of techniques for detecting image forgeries in image processing. It begins with an introduction to digital images and image processing. It then reviews several papers that have proposed various techniques for image forgery detection including pixel-based detection, key point-based detection, and detection of copy-move forgeries. The document also describes challenges in digital image processing and different categories of image forgery detection techniques. It concludes that accurate methods are needed to detect image forgeries using image processing approaches and reviews can help improve existing techniques.
A Review on Overview of Image Processing Techniquesijtsrd
Image processing is actually among the fast growing innovations across various areas of a business with applications. Image processing frequently forms key scientific areas within the areas of electronics and computer science. Image processing is a tool for refining raw photographs obtained in our everyday lives from rockets, ships, space samples or military identification flights. Thanks to technologically powerful personal computers, broad databases of current devices and the Graphic Technology and the accessible resources for such software and apps, this area is strong and common. The provided input is an image and its output an enhanced high quality image according to the techniques used in the image processing procedure. Image processing is typically called digital image processing, although it is often possible to optically process and analogy photograph. An overview of image processing methods is given in this article. This article focuses mainly on identifying specific methods utilized in various image processing phases. Hirdesh Chack | Vijay Kumar Kalakar | Syed Tariq Ali "A Review on Overview of Image Processing Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31819.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/31819/a-review-on-overview-of-image-processing-techniques/hirdesh-chack
Image processing is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within electronics engineering and computer science disciplines too. Image Processing is a technique to enhance raw images received from satellites, space probes, aircrafts, military reconnaissance flights or pictures taken in normal day-to-day life from normal cameras. The field is becoming powerful and popular because of technically powerful personal computers, large memories of available devices as well as graphic softwares and tools available with that devices and gadgets. Image acquisition, pre-processing, segmentation, representation, recognition and interpretation are the different basic steps through which image processing is carried out. [3][4].
Image processing is the process of transforming an image into a digital form and performing certain operations to get some useful information from it. The image processing system usually treats all images as 2D signals when applying certain predetermined signal processing methods.There are five main types of image processing Visualization Find objects that are not visible in the imageRecognition Distinguish or detect objects in the imageSharpening and restoration Create an enhanced image from the original imagePattern recognition Measure the various patterns around the objects in the imageRetrieval Browse and search images from a large database of digital images that are similar to the original image Supriya Kumari "Image Processing in the Current Scenario" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-5 , August 2022, URL: https://www.ijtsrd.com/papers/ijtsrd51728.pdf Paper URL: https://www.ijtsrd.com/computer-science/other/51728/image-processing-in-the-current-scenario/supriya-kumari
Discover the fundamentals, Characteristics & types of digital image analysis. Learn about pixels, bit depth, challenges, and AI impacts on image processing.
A Review on Overview of Image Processing Techniquesijtsrd
Image processing is actually among the fast growing innovations across various areas of a business with applications. Image processing frequently forms key scientific areas within the areas of electronics and computer science. Image processing is a tool for refining raw photographs obtained in our everyday lives from rockets, ships, space samples or military identification flights. Thanks to technologically powerful personal computers, broad databases of current devices and the Graphic Technology and the accessible resources for such software and apps, this area is strong and common. The provided input is an image and its output an enhanced high quality image according to the techniques used in the image processing procedure. Image processing is typically called digital image processing, although it is often possible to optically process and analogy photograph. An overview of image processing methods is given in this article. This article focuses mainly on identifying specific methods utilized in various image processing phases. Hirdesh Chack | Vijay Kumar Kalakar | Syed Tariq Ali "A Review on Overview of Image Processing Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31819.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/31819/a-review-on-overview-of-image-processing-techniques/hirdesh-chack
Image processing is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within electronics engineering and computer science disciplines too. Image Processing is a technique to enhance raw images received from satellites, space probes, aircrafts, military reconnaissance flights or pictures taken in normal day-to-day life from normal cameras. The field is becoming powerful and popular because of technically powerful personal computers, large memories of available devices as well as graphic softwares and tools available with that devices and gadgets. Image acquisition, pre-processing, segmentation, representation, recognition and interpretation are the different basic steps through which image processing is carried out. [3][4].
Image processing is the process of transforming an image into a digital form and performing certain operations to get some useful information from it. The image processing system usually treats all images as 2D signals when applying certain predetermined signal processing methods.There are five main types of image processing Visualization Find objects that are not visible in the imageRecognition Distinguish or detect objects in the imageSharpening and restoration Create an enhanced image from the original imagePattern recognition Measure the various patterns around the objects in the imageRetrieval Browse and search images from a large database of digital images that are similar to the original image Supriya Kumari "Image Processing in the Current Scenario" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-5 , August 2022, URL: https://www.ijtsrd.com/papers/ijtsrd51728.pdf Paper URL: https://www.ijtsrd.com/computer-science/other/51728/image-processing-in-the-current-scenario/supriya-kumari
Discover the fundamentals, Characteristics & types of digital image analysis. Learn about pixels, bit depth, challenges, and AI impacts on image processing.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Reviewing the Effectivity Factor in Existing Techniques of Image Forensics IJECEIAES
Studies towards image forensics are about a decade old and various forms of research techniques have been presented till date towards image forgery detection. Majority of the existing techniques deals with identification of tampered regions using different forms of research methodologies. However, it is still an open-end question about the effectiveness of existing image forgery detection techniques as there is no reported benchmarked outcome till date about it. Therefore, the present manuscript discusses about the most frequently addressed image attacks e.g. image splicing and copy-move attack and elaborates the existing techniques presented by research community to resist it. The paper also contributes to explore the direction of present research trend with respect to tool adoption, database adoption, and technique adoption, and frequently used attack scenario. Finally, significant open research gap are explored after reviewing effectiveness of existing techniques.
Image Forgery Detection Using Feature Point Matching and Adaptive Over Segmen...dbpublications
A duplicate move fabrication
location conspire utilizing highlight point
coordinating and versatile over-division is
worked here. This plan coordinates both
square based and key point-based falsification
location strategies. To start with, the proposed
Adaptive Over-Segmentation calculation
fragments the host picture into non-covering
and sporadic pieces adaptively. At that point,
the component focuses are removed from each
piece as square elements, and the square
elements are coordinated with each other to
find the named include focuses, this strategy
can around show the presumed fraud districts.
To recognize the phony locales all the more
precisely, the Forgery Region Extraction
calculation is exhibited, which replaces the
component focuses with little superpixels as
highlight pieces. At that point combines the
neighboring hinders that have comparable
nearby shading highlights into the component
squares to create the blended areas. At last, it
applies the morphological operation to the
combined locales to create the identified
fabrication areas. The trial comes about show
that the proposed duplicate move falsification
identification plan can accomplish much better
location comes about even under different
testing conditions contrasted and the current
cutting edge duplicate move fabrication
discovery strategies.
A New Copy Move Forgery Detection Technique using Adaptive Over-segementation...journalBEEI
With the development of Image processing editing tools and software, an image can be easily manipulated. The image manipulation detection is vital for the reason that an image can be used as legal evidence, in the field of forensics investigations, and also in numerous various other fields. The image forgery detection based on pixels aims to validate the digital image authenticity with no aforementioned information of the main image. There are several means intended for tampering a digital image, for example, copy-move or splicing, resampling a digital image (stretch, rotate, resize), removal as well as the addition of an object from your image. Copy move image forgery detection is utilized to figure out the replicated regions as well as the pasted parts, however forgery detection may possibly vary dependant on whether or not there is virtually any post-processing on the replicated part before inserting the item completely to another party. Typically, forgers utilize many operations like rotation, filtering, JPEG compression, resizing as well as the addition of noise to the main image before pasting, that make this thing challenging to recognize the copy move image forgery. Hence, forgery detector needs to be robust to any or all manipulations and also the latest editing software tools. This research paper illustrates recent issues in the techniques of forgery detection and proposes a advanced copy–move forgery detection scheme using adaptive over-segmentation and feature point matching. The proposed scheme integrates both block-based and key point-based forgery detection methods.
Analysis and Detection of Image Forgery Methodologiesijsrd.com
"Forgery" is a subjective word. An image can become a forgery based upon the context in which it is used. An image altered for fun or someone who has taken a bad photo, but has been altered to improve its appearance cannot be considered a forgery even though it has been altered from its original capture. The other side of forgery are those who perpetuate a forgery for gain and prestige. They create an image in which to dupe the recipient into believing the image is real and from this they are able to gain payment and fame. Detecting these types of forgeries has become serious problem at present. To determine whether a digital image is original or doctored is a big challenge. To find the marks of tampering in a digital image is a challenging task. Now these marks of tampering can be done by various operations such as rotation, scaling, JPEG compression, Gaussian noise etc. called as attacks. There are various methods proposed in this field in recent years to detect above mentioned attacks. This paper provides a detailed analysis of different approaches and methodologies used to detect image forgery. It is also analysed that block-based features methods are robust to Gaussian noise and JPEG compression and the key point-based feature methods are robust to rotation and scaling.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Reviewing the Effectivity Factor in Existing Techniques of Image Forensics IJECEIAES
Studies towards image forensics are about a decade old and various forms of research techniques have been presented till date towards image forgery detection. Majority of the existing techniques deals with identification of tampered regions using different forms of research methodologies. However, it is still an open-end question about the effectiveness of existing image forgery detection techniques as there is no reported benchmarked outcome till date about it. Therefore, the present manuscript discusses about the most frequently addressed image attacks e.g. image splicing and copy-move attack and elaborates the existing techniques presented by research community to resist it. The paper also contributes to explore the direction of present research trend with respect to tool adoption, database adoption, and technique adoption, and frequently used attack scenario. Finally, significant open research gap are explored after reviewing effectiveness of existing techniques.
Image Forgery Detection Using Feature Point Matching and Adaptive Over Segmen...dbpublications
A duplicate move fabrication
location conspire utilizing highlight point
coordinating and versatile over-division is
worked here. This plan coordinates both
square based and key point-based falsification
location strategies. To start with, the proposed
Adaptive Over-Segmentation calculation
fragments the host picture into non-covering
and sporadic pieces adaptively. At that point,
the component focuses are removed from each
piece as square elements, and the square
elements are coordinated with each other to
find the named include focuses, this strategy
can around show the presumed fraud districts.
To recognize the phony locales all the more
precisely, the Forgery Region Extraction
calculation is exhibited, which replaces the
component focuses with little superpixels as
highlight pieces. At that point combines the
neighboring hinders that have comparable
nearby shading highlights into the component
squares to create the blended areas. At last, it
applies the morphological operation to the
combined locales to create the identified
fabrication areas. The trial comes about show
that the proposed duplicate move falsification
identification plan can accomplish much better
location comes about even under different
testing conditions contrasted and the current
cutting edge duplicate move fabrication
discovery strategies.
A New Copy Move Forgery Detection Technique using Adaptive Over-segementation...journalBEEI
With the development of Image processing editing tools and software, an image can be easily manipulated. The image manipulation detection is vital for the reason that an image can be used as legal evidence, in the field of forensics investigations, and also in numerous various other fields. The image forgery detection based on pixels aims to validate the digital image authenticity with no aforementioned information of the main image. There are several means intended for tampering a digital image, for example, copy-move or splicing, resampling a digital image (stretch, rotate, resize), removal as well as the addition of an object from your image. Copy move image forgery detection is utilized to figure out the replicated regions as well as the pasted parts, however forgery detection may possibly vary dependant on whether or not there is virtually any post-processing on the replicated part before inserting the item completely to another party. Typically, forgers utilize many operations like rotation, filtering, JPEG compression, resizing as well as the addition of noise to the main image before pasting, that make this thing challenging to recognize the copy move image forgery. Hence, forgery detector needs to be robust to any or all manipulations and also the latest editing software tools. This research paper illustrates recent issues in the techniques of forgery detection and proposes a advanced copy–move forgery detection scheme using adaptive over-segmentation and feature point matching. The proposed scheme integrates both block-based and key point-based forgery detection methods.
Analysis and Detection of Image Forgery Methodologiesijsrd.com
"Forgery" is a subjective word. An image can become a forgery based upon the context in which it is used. An image altered for fun or someone who has taken a bad photo, but has been altered to improve its appearance cannot be considered a forgery even though it has been altered from its original capture. The other side of forgery are those who perpetuate a forgery for gain and prestige. They create an image in which to dupe the recipient into believing the image is real and from this they are able to gain payment and fame. Detecting these types of forgeries has become serious problem at present. To determine whether a digital image is original or doctored is a big challenge. To find the marks of tampering in a digital image is a challenging task. Now these marks of tampering can be done by various operations such as rotation, scaling, JPEG compression, Gaussian noise etc. called as attacks. There are various methods proposed in this field in recent years to detect above mentioned attacks. This paper provides a detailed analysis of different approaches and methodologies used to detect image forgery. It is also analysed that block-based features methods are robust to Gaussian noise and JPEG compression and the key point-based feature methods are robust to rotation and scaling.
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A Review Paper On Image Forgery Detection In Image Processing
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 4, Ver. I (Jul.-Aug. 2016), PP 86-89
www.iosrjournals.org
DOI: 10.9790/0661-1804018689 www.iosrjournals.org 86 | Page
A Review Paper on Image Forgery Detection In Image Processing
Shivani Thakur1
Ramanpreet Kaur2
Dr. Raman Chadha3
Jasmeet Kaur4
1,4
M.tech student, CGCTC, Jhanjeri, Mohali
2
Assistant Professor CGCTC, Jhanjeri, Mohali
3
Professor, Head(CSE), Jhanjeri, Mohali
Abstract: The image forensics is the technique which is applied to hide image important information. In the
base paper, the technique of SIFT algorithm is applied to mark the objects in the image. In the SIFT algorithm
whole image is scanned and from the scanned image objects are marked. The properties of the marked object
are accessed and objects which have similar properties are classified into group and other are into second. To
classify the similar type of objects techniques like block based & Key Point based technique, shift key point can
be used.
Keywords: Image Processing, image forensics, digital signature, image preprocessing.
I. Introduction
A digital image is defined as a 2D function i.e. f(x,y) where (x,y) shows the spatial coordinates and the
amplitude of f at any point (x,y) known as the intensity or gray level of image at that particular point. In case
when x,y and the amplitude value of f are finite and discrete quantities, we can call that image as a digital
image. Basically, an image i.e. processed by a digital computer is called as a digital image. It may be noted that
a digital image consists of a finite number of elements which are having a particular location and value. These
elements of image are known as image elements, picture elements or pixels.
Image processing is a technique in which the image is converted into digital form and some operations are
performed on it for the purpose of getting and enhanced image or extracting some meaningful or useful
information from it. It is a kind of signal processing in which the input may be image e.g. video frame,
photograph and .output may possibly be the image or some characteristics related with the image. Image
processing involves the following three steps:
1. Involves importing the image via using image acquisition tool which may be optical scanner or digital
photography.
2. Now the image is analyzed and manipulated which involves data compression and image enhancement.
3. Last stage is output which involves the result i.e. altered image. There are two methods that are used for
image processing:
i. Analog image processing
ii. Digital image processing
i. Analog image processing
It may be used for hard copies i.e. printouts or photographs etc.
ii. Digital image processing
It is the process of manipulating the digital image using computers.
Fig1. Digital image processing
II. Literatute Review
This review paper provides a survey on different image forensics techniques which are given in
previous papers. In this paper [1], they have proposed methodologies to identify these images and find out the
fake region of the forgery image. They have developed algorithm depend upon the concept of abnormal
anomalies and identify the forgery regions.
2. A Review Paper on Image Forgery Detection In Image Processing
DOI: 10.9790/0661-1804018689 www.iosrjournals.org 87 | Page
In this paper [2], first of all classification of image forgery detection technique has been discussed. After that
pixel based detection is also defined. A technique for copy-move forgery detections discussed. But this
technique is applied on shifted region only. Proposed technique is developed to cover all the limitation of the
both the techniques and fast copy moving technique.
In this paper [3], they reviewed the technique to remove shift key point attacks from the image for the
betterment of SIFT-based copy–move forgery detection. To handle these types of attacks three forensic
techniques have discussed in this paper. They apply the detectors to a practical image forensic scenario of SIFT-
based copy-move forgery detection to assume the SIFT-based detectors and as a result give new proposed
technique.
In this paper [4], they explained that it is very easy to tamper the images. Image forensic can be used to
determine the protection of the image. They have discussed the various copy move forgery detection techniques
which includes Block based & Key Point based techniques.
In this paper [7], they discussed passive approach to detect digital forgeries by checking its artifact
consistencies. JPEG image compression could be used as a natural authentication code for blocking artifact. A
technique has been proposed based on estimated quantized table using power spectrum of the DCT coefficient
histogram. Experiments have been done to validate proposed techniques and in future discovery of other image
quality consistencies is measured.
In this paper [6] they classified the image forgery detection technique. Later on they also discussed two
important techniques for the pixel based forgery detection. In this paper they also have discussed copy-move
forgery detection technique. This technique only deals with shifting of copied regions. So there is a need of
another technique for fast copy move detection and it is also discussed in this paper. At the end both techniques
are compared and analyzed.
III. Various Techniques Of Image Processing
Various techniques of the image processing are:
1. Image Representation
2. Image Preprocessing
3. Image Enhancement
4. Image Analysis
5. Image Segmentation
6. Image Restoration
7. Image Compression
1. Image Representation
In the real world image is defined as a function of two real variables. We can say that f(x,y) with f as
the amplitude or brightness of the image at the real coordination position (x,y). In most cases f(x,y) which is
lying on the face of the sensors. Typically an image file such as JPEG, BMP, TIFF etc [2], has some header and
picture information. A header generally consists details like format identifier, number of bits/pixel, resolution,
compression type etc.
2. Image Preprocessing
The main aim of preprocessing is an improvement of image data which is used to remove unwanted
images and distortions from the images for image processing.
3. Image Enhancement
Sometimes images which are obtained from satellites and cameras have poor quality of brightness and
contrast because limitations of imaging sub system and illumination while capturing image. Image has different
types of noise. In image enhancement, the goal is to accentuate certain image features for subsequent analysis or
for image display [1,2].
4. Image Analysis
Image Analysis is concerned with quantitative measurement of the image to make it perfect and noise
free. It requires extraction of certain features for the identification of the object. Segmentation techniques are
used to isolate desired objects from the scene to make them perfect [5].
5. Image Segmentation
Image segmentation is the process on which image can be divided into number of its subparts. The
problem which is being solved is responsible for the division of the object identification.
3. A Review Paper on Image Forgery Detection In Image Processing
DOI: 10.9790/0661-1804018689 www.iosrjournals.org 88 | Page
6. Image Restoration
It is concerned with filtering the observed image to minimize the effect of degradations. Effectiveness
of image restoration depends on the extent and accuracy of the knowledge of degradation process as well as on
filter design. Image restoration differs from image enhancement in that the latter is concerned with more
extraction or accentuation of image features.
7. Image Compression
It is concerned with minimizing the no of bits required to represent an image. Application of
compression are in broadcast TV, remote sensing via satellite, military communication via aircraft, radar,
teleconferencing, facsimile transmission, for educational & business documents , medical images that arise in
computer tomography, magnetic resonance imaging and digital radiology, motion , pictures ,satellite images,
weather maps, geological surveys and so on [2].
IV. Challenges In Digital Image Processing
1. Compression: The image storage and transmission involves the use of digital techniques 2.
Enhancement: In case of enhancement the quality of image is improved. The quality of image may be poor in
terms of contrast which may be low, image may be noisy or it may be blurred etc. In order to overcome this,
many algorithms have been used .But difficult part is how we can remove the degradation without hurting the
signal. A major challenge is in digital image processing is how can we enhance severely degraded images. 3.
Recognition: An image recognition system means to classify input pattern into one of a set of pre-specified
classes. This task is easy in case of number of classes is small and if the members in the same class are almost
same. But difficulty level increases if the number of classes is large or if the member in same class can look
very different.4. Visualization: The main task of visualization is to generate images based on three dimensional
object and scene object. The main challenge is how we can model dynamic scenes containing non-grid objects.
The model should be realistic and the computation cost should be reasonable.
V. Image Forgery Detection
Nowadays it is easy to remove and add some elements from the image for the purpose to manipulate
and to get some good results of image forgeries. In image processing, different types of software are used. Some
software can change a particular block of image without affecting the originality of the image. This kind of
modification cannot be noticed by human eye. The main task is to verify the original image. For the purpose of
manipulating an image various techniques of image processing like scaling, rotation, blurring, filtering and
cropping can be used. The image forgery detection is required in various fields of image processing. Image
forgery detection is raising research field with important applications for ensuring the credibility of digital
images.Image processing can be divided into two categories:
a. Active Approach
b. Passive Approach
a. Active Approach: In active approach, some preprocessing of digital image like embedded watermark or
signature generation is required at the time of creating image and limits its applications. This approach is not
used for authentication purpose.
b. Passive Approach: In the passive approach, digital signature is not used for the purpose of authentication. In
this technique some assumptions are used that digital forensics may not leave any visual clue for tempering the
image. It may alter the underlying statistics of image. The image forensics tools can be grouped into five
categories:
i. Pixel based technique
ii. Format based technique
iii. Camera based technique
iv. Physically based technique
v. Geometric based technique
VI. Comparison Table
Author Year Description Outcome
S. Murali et al [1] 2012 methodologies to identify these
images and find out the fake
region of the forgery image.
algorithm depend upon the concept of
abnormal anomalies and identify the
forgery regions.
Andrea Costanzo et.al [3] 2014 To handle shift key point of
attacks three forensic techniques
have discussed.
apply the detectors to a practical image
forensic scenario of SIFT-based copy-
move forgery detection to assume the
SIFT-based detectors .
4. A Review Paper on Image Forgery Detection In Image Processing
DOI: 10.9790/0661-1804018689 www.iosrjournals.org 89 | Page
Ms. P. G.Gomase, Ms. N. R.
Wankhade [2]
2014 pixel based detection is defined No method achieved 100% robustness
against post processing operations.
Rohini.A.Maind et.al [5] 2014 four features are extracted to
reduce the dimensions
do blurring and remove noise from the
image with low complexity
Gagandeep Kaur, Manoj
Kumar [4]
2015 various copy move forgery
detection techniques
Block based & Key Point based
techniques.
VII. Conclusion
In order to detect image forgery, an accurate and successful method should be used and this can be
done with the help of image processing a approach. This paper reviewed various techniques which have been
already used. These techniques are related to segmentation and classification. Using these methods,
identification image forgeries has been accurately done but still having some chances for the improvements in
the existing techniques.
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