Detection of Copy Move Forgery

Detection of Copy Move Forgery J.Reethrose B.E., Dr. J. P. Ananth M.E., Ph.D., Abstract—Digital images are easy to manipulate and edit using some editing software. So it is difficult to identify the duplicate images. Copy-move manipulations are common form of local processing, where parts of an image are copied and reinserted into another part of the same image. The problem of detecting the copy-move forgery describes an efficient and reliable detection and detects duplicate image regions. Most detection algorithm focused on pixel basis. In this paper propose a new approach to detect forgery image such scale, rotate, etc. Keywords—copy-move forgery, SIFT, LSH, RANSAC. INTRODUCTION Copy-move forgery is one of image tampering, were a part of the image is copied and pasted on another part of the same image. This copy-move forgery is easily done by some editing software such as Adobe Photoshop. Normally the human eye does not easily find out the copied region. The regions may be scaling or rotation type of manipulations. The goal of copy-move forgery is detecting duplicate image regions. The most common image manipulation techniques involve the following Removal of objects from the image. Addition of objects in the image. Change the objects appearance in the image. The most common of these three manipulations is removal of undesired objects from the image. Digital image forgery detection techniques are classified into active and passive approaches. In active approach, the digital image requires some pre-processing such as watermark embedding or signature generation at the time of creating the image, which would limit of their application in practice. Moreover, there are millions of digital images in internet without digital signature or watermark. In such scenario active approach could not be used to find the authentication of the image. Unlike the watermark-based and signature-based methods; the passive technology does not need any digital signature generated or watermark embedded in advance. Fig 1.1 Classification of Forgery detection techniques GENERAL DETECTION PROCEDURE Copy move manipulations result in duplicate image regions, which practical forensic analyses examine in terms of robust feature representations of parts of the image. Analyzing the image is very important before the preprocessing. After optional preprocessing (e.g., color to grayscale conversion), the image is transformed to the feature space. Feature representation is finding the duplicate region. There are so many methods used to find the duplicate image such as DCT (Discrete Cousine Transform), DWT (Discrete Wavelet Transform), and PCD (Principal Component Analysis). A set of feature vectors represents local image characteristics and is inspected for similarities in a matching procedure. This is achieved either by splitting the image into small blocks, which are then transformed separately, or by finding salient key points and extracting feature vectors based thereon. The matching procedure is finding the similarity of duplicate image blocks. Some of the matching algorithms are k- d tree, Sorting, Nearest Neighbour Search, and Hashing. Similar feature vectors or their corresponding coordinates in the image plane. False positives in the matching procedure are pruned in a final error reduction step. The error reduction step is finding the duplicate image region. Fig 2.1 General copy move detection pipeline PROPOSED SYSTEM Accordingly, digital image forensics has emerged as a new research field that aims to reveal tampering operations in digital images. A common manipulation in tampering with digital images is known as region duplication, where a continuous portion of pixels is copied and pasted to a different location in the same image. To make convincing forgeries, the duplicated regions are often created with geometrical or illumination adjustments. There are various method used in the existing system. DWT (Discrete Wave Transform) used to reduce dimensionality reduction. But it does not find the rotation and scaling. Lexicographic Sorting and Counting Bloom Filters are also used in the existing system. But it cannot find solution of scaling and rotation. It does not remove the noise. The Zernike moment is easy way to find the copy (-rotate-) move forgery. This method is still weak against scaling or the other tempering based on Affine transform. Existing System has the drawback of computational com plexity and does not find accuracy of the duplicate image regions. In recent years, several methods have been proposed to detect region duplication for the purpose of image forensics. These methods are based on finding pixel blocks that are exact copies of each other in an image. Such methods are most effective for the detection of region copy-move, where a region of pixels is pasted without any change to another location in the image. A common form of digital tampering is Copy-Move forgery, in which a part of the image itself is copied and pasted into another part of the same image to conceal an important object. Because the copied part come from the same image, its important properties, such as noise, Shape, color and texture, will be compatible with the rest of the image and thus will be more difficult to distinguish and detect. In the preprocessing stage the RGB image is converted into grayscale image. Apply SIFT algorithm using to find the keypoints. SIFT Algorithm is used to detect the keypoint localization. Good keypoints and features should represent distinct locations in an image, be efficient to compute and robust to local geometrical distortion, noise, illumination variations and other degradations. Here, present SIFT features detection method to find the duplicate. Specifically, to detect the locations, of potential duplicated regions, we first detect SIFT keypoints in an image. The detected keypoints are matched using hashing algorithm. We can use the matched SIFT keypoints to estimate the affine transform parameters, but the obtained results are inaccurate due to the large number of mismatched keypoints. To find out the unreliable keypoints we use Random Sample Consensus (RANSAC) algorithm then use the Affine transform. Finally detect the duplicate region. The following diagram shows the way to find the copy move forgery. Raw image is considered as the forgery image. Normally the raw image is RGB image. That RGB image is converting into gray scale. This is the preprocessing stage. Noise removal also includes the preprocessing stage. The steps involved in proposed method as follows. First step to find out the keypoints using SIFT (Scale Invariant Feature Transform). Find the keypoints then perform the matching keypoints procedure. Matching keypoints is using the Locality Sensitive Hashing (LSH). Matching is easy to find out the hash buckets. This hash is found the similar values or keypoints. Duplicate region is detected after matching. Find the duplicate region using the RANSAC (RANdom SAMple Consensus) algorithm. Fig 3.1 Block diagram of forgery detection A. Finding keypoints In the preprocessing stage the RGB image is converted into grayscale image. Apply SIFT algorithm for finding the keypoints. SIFT algorithm consist of the following stages: Scale-space extrema detection Keypoint localization Orientation assignment Generation of keypoint descriptors Good keypoints and features should represent distinct locations in an image, be efficient to compute and robust to local geometrical distortion, illumination variations, noise and other degradations. Here, to present a new region duplication detection methods based on the image SIFT features. Specifically, to detect the locations, of potential duplicated regions, first detect SIFT keypoints in an image. And compute the SIFT features for such keypoints. To ensure the obtained feature vector invariant to rotation and scaling, the size of the neighborhood is determined by the dominant scale of the keypoint, and all gradients within are aligned with the keypoints dominant orientation dominant orientation. B. Matching keypoints The similar keypoints can be found out using Locality Sensitive Hashing (LSH) technique. Previous year a k-d tree algorithm used to detect the keypoint. This is taken more time search to compute the similar values. Locality Sensitive Hashing easy to detect the similar values. Locality-sensitive hashing(LSH) is a method of performing probabilisticdimension reductionof high-dimensional data. The basic idea is tohashthe input items so that similar items are mapped to the same buckets with high probability (the number of buckets being much smaller than the universe of possible input items). This is different from the conventional hash functions, such as those used incryptographyas in this case the goal is to maximize probability of collision of similar items rather than avoid collisions. C. Duplicate Region RANSAC algorithm used to detect the error. This means SIFT produce the keypoints then Locality Sensitive Hashing used to find the similar keypoints. Locality Sensitive Hashing has the bucket. Each bucket contains the index that index contain the values of keypoints. RANSAC algorithm reduces the error. Instead of RANSAC using the Affine transformation. So it will easily to find out the error of scale, rotation and transformation of copy move forgery detection. CONCLUSION In particular the human eye does not easily find out the copied region. The regions may be scaling or rotation type of manipulations. The goal of copy-move forgery is detecting duplicate image regions. Copy move forgery is difficult to identify the duplicate image region. SIFT is used to detect the keypoints of given image. SIFT is Scale Invariant Feature Transform. So it focused to detect the Scale and transformation. Good keypoints and features should represent distinct locations in an image, be efficient to compute and robust to local geometrical distortion, illumination variations, noise and other degradations. Here, we present a new region duplication detection method based on the image SIFT features. Locality Sensitive Hashing detects the similar keypoints. Finally RANSAC algorithm used to find the duplicate image region. REFERENCE [1] Rohini. R. Maind, Alka Khade, D. K. Chitre â€Å"Robust Image Copy move Forgery Detection† International Journal of Advanced and Innovative Research (IJAIR) ISSN: 2278-7844, Vol. 2, Issue 8, 2013. [2] Yanjun Cao, Tiegang Gao , Li Fan , Qunting Yang â€Å"A robust detection algorithm for copy-move forgery in digital images† Forensic Science International 214 (2012). [3] Reza Oji â€Å"An Automatic Algorithm for Object Recognition and Detection Based On ASIFT Keypoints† Signal Image Processing: An International Journal (SIPIJ) Vol.3, No.5, October 2012. [4] Pradyumna Deshpande, Prashasti Kanikar, â€Å"Pixel Based Digital Image Forgery Detection Techniques† International Journal of Engineering Research and Applications (IJERA) Vol-2, Issue 3, May-June 2012. [5] B.L.Shivakumar, Dr. S.Santhosh Baboo, â€Å"Automated Forensic Method for Copy-Move Forgery Detection based on Harris Interest Points and SIFT Descriptors† International Journal of Computer Applications (0975 – 8887) Volume 27– No.3, August 2011 [6] Xunyu Pan and Siwei Lyu,† Detecting Image Region Duplication Using Sift Features† IEEE, ICASSP, Dallas, USA 2010. [7] Seung-Jin Ryu, Min-Jeong Lee, and Heung-Kyu Lee, â€Å"Detection of Copy-Rotate Move Forgery Using Zernike Moments† International Conference on Information Hiding 2010. [8] Saiqa Khan, Arun Kulkarni, â€Å"Reduced Time Complexity for Detection of Copy-Move Forgery Using Discrete Wavelet Transform† International Journal of Computer Applications (0975 – 8887) Volume 6– No.7, September 2010. [9] Sevinc Bayram, Husrev Taha Sencar, Nasir Memon, â€Å"An Efficient and Robust Method for Detecting Copy-Move Forgery† International Conference on Acoustics, Speech, and Signal Processing – 2009. [10] Tehseen Shahid, Atif Bin Mansoor â€Å"Copy-Move Forgery Detection Algorithm for Digital Images and a New Accuracy Metric† International Journal of Recent Trends in Engineering, Vol 2, No. 2, November 2009. [11] Aristides gionis, piote indyk, Rajeev motwani â€Å"Similarity search in high dimension via hashing 1999. [12] Prof. Unmukh Datta, Chetna Sharma â€Å"Analysis of Copy-Move Image Forgery Detection† International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE) Volume 2, Issue 8, August 2013 [13] Frank Y. Shih and Yuan Yuan â€Å"A Comparison Study on Copy-Cover Image Forgery Detection† The Open Artificial Intelligence Journal, 2010, 4, 49-54 49

Comparing the Act of Creation in Grendel and Frankenstein Essay

The Act of Creation in Grendel and Frankenstein   Ã‚   Man has always been driven to create. We constantly shape the world around us by inventing stories of heroes and monsters, by crafting complex but passionate ideals about good and evil. Some relish in the power that this manipulation of reality wields; others are more innocent in that they are simply yielding to a universal longing for something in which to believe.    In both John Gardner's Grendel and Mary Shelley's Frankenstein, creation is a central theme. Victor Frankenstein is inexplicably driven to make a creature like himself, though he doesn't have any external reason for doing so. The monster himself enacts a kind of creation; he seeks to understand the truth of human nature by reading man's works, but also indulges in his own stories and fantasies of a life lived among friends. Shelley explores to some extent the morality of such creation (at least on the part of Victor Frankenstein), but Gardner is more interested in what the act of creation reveals about the nature of existence.    In Grendel, nearly all of the characters are driven to shape the world to their ideas. Hrothgar spends his life crafting a government. Grendel's mother is described as loving her son "not for myself, my holy specialness, but for my son-ness, my displacement of air as visible proof of her power (138)." Both Grendel and the Shaper constantly seek the ability to reshape reality with words. While they have differing motives, all of these acts of creation give power and significance to the creator. As Baby Grendel desperately convinces himself, it is the act of observing and commenting on what is outside that makes one real: "I understood that, finally ... ...endel would undoubtedly un-create if he really had that power. He understands too late. His death is as necessary as the death of a tree in winter; a new morning lies in wait for the Danes, as it does for all men in the circle of living and dying.    Works Cited and Consulted    Boyd, Stephen. York Notes on Mary Shelley's Frankenstein. Longman York Press, 1992.    Gardner, John. Grendel. Vintage Books, 1989.    Patterson, Arthur Paul. A Frankenstein Study. http://www.watershed.winnipeg.mb.ca/Frankenstein.html    Shelley, Mary. Frankenstein or the Modern Prometheus. Edited with an Introduction and notes by Maurice Hindle. Penguin books, 1992      Strehle, Susan. "John Gardner's Novels: Affirmation and the Alien." Contemporary Literary Criticism. Ed. Dedria Bryfonski. Vol. 10. Detroit: Gale Research, 1979. 218 -219.

Effects of Stress on Grades

Students at universities worldwide oftentimes find stress to be a part of everyday life. Stress is defined as the way one responds to the changes and demands of life either emotionally, physically, or mentally. Stress is registered in one’s â€Å"fight or flight† response. When an exciting or dangerous event occurs changes take place in the body to prepare the person to deal with the stressful situation. After the stressful situation has subsided the body returns to a normal state. The constant stress of being a college student does not allow the body to return to a normal state so a student may never be able to fully relax. This can lead to stress overload (Bower, 2010). Many factors can affect a student’s academic performance and grades. The National College Health Assessment of 2004 shows that the most significant impediment to effective listening, retaining information, and studying is stress. Stress is noted to be the number one cause of poor academic functioning in a student above other problems like depression, illness, eating disorders, death of a family member, and even sexual assault. The study reviewed 47,202 college students and 32. 4% listed stress as the number one barrier to schoolwork (Temple, 2006). Many college students have multiple stressors. Most are taking multiple classes, working full-time jobs, have family members to take care of, are working long hours at unpaid internship sites, or any combination of these. Many college students must deal with the stress of just leaving home and no longer benefiting from familial support. Relationship problems may begin to develop between the student and the friends, families, or significant others that have been left at home. This overload of responsibility and worry can lead to a lack of sleep and improper nutrition, which can cause difficulty in school (Bower, 2010). Proper nutrition may become a problem for a student because he or she may be unable to grocery shop on a regular basis. Other problems with nutrition occur because a student who is living in a dormitory may be unable to cook proper meals and unable to store large quantities of food. Some students new to living without parents may not have the knowledge to cook a decent meal. Others simply do not have the time to eat properly. Without proper nutrition the brain does not function properly and the student may have difficulty concentrating on schoolwork (Womble, 2002). Maintaining employment while attending college can also be a source of stress. This stress may come from working long hours that can make the student too tired to focus on his or her studies or working long hours may lead to attendance problems at school. Mentally focusing on both work life and school life can be exhausting for a student and can lead to increased amounts of stress. The number of hours a student spends at work can be directly related to that student’s grade point average (GPA) because the more time a student spends at work, the less time that student can spend studying (Womble, 2002). Sleep, or lack of, is the most important factor on a student’s GPA. Many college students do not sleep enough during the week to properly rest the body and mind. Lack of sleep has been shown to increase anxiety and stress. Simple sleep patterns like waking earlier during the weekdays than on the weekends have also been shown to affect the GPA of a student (Womble, 2002). Not all college students complain of experiencing stress, many do. Although some stress is good for a person and may be energizing or motivating, it is important for a person to recognize and be able to manage bad stress before it spirals out of control and has a negative effect. Coping mechanisms are important for anyone but may prove to be more so for a college student. Coping mechanisms include sleeping enough, spending time doing fun activities, relaxing, and practicing time management. Developing ones communication, writing, and test taking skills is important to reduce stress. Engaging in physical activity, reading a book that is not school related, or getting a massage are ways to reduce stress and relax. Daily use of a planner to track assignment due dates and upcoming project deadlines is useful for staying on track with studies (Bower, 2010). Coping mechanisms come from within, from something called personality hardiness. The idea of personality hardiness first came to be with regard to protecting business executives from the health effects of stress. This concept involves having a sense of control and commitment. Commitment means that a person can view the world as a meaningful place and he or she seeks to be involved in the world rather than withdrawn from it. Control shows that a person believes he or she can influence events that take place in his or her world. Personality hardiness means that a person may not feel threatened by changes to his or her environment. Theoretically, a student with personality hardiness should be able to adapt to the changes that come with enrollment in school, taking multiple classes, maintaining employment, and family obligations without stress overload. The result should mean that a student takes on the new challenges with less stress and instead turns the stressful events into opportunities for growth and personal development (Hystad, Eid, Laberg, Johnsen, & Bartone, 2009). Two studies have been performed by Lifton and colleagues. These studies assessed the personality hardiness of individuals throughout the college years. These studies had newly arriving college students complete hardiness measures and found a positive interrelationship between persistence and the student’s graduation date four years later. The hardiness scores among those who did not complete four years of college were lower than those who did not drop out. The scores on the hardiness exams were not directly related to scores on entrance exams or high academic ability. Personality hardiness is not based on a person’s academic ability but rather a person’s attitude or the manner in which he or she approaches life’s challenges (Hystad et al. , 2009). Though the information contained in the numerous studies that have been done regarding stress and the college student’s ability to achieve a decent GPA is helpful to understanding stress and how it affects different people there are always exceptions to every rule. Although it is true that every person handles stressful situations in his or her own unique way there are many resources available to help a college student achieve passing grades regardless of the stress factor. At the same time, there are many choices a college student makes that adds to the amount of stress he or she carries in everyday life. Many times when a college student is sleep deprived it is that he or she has made the choice to be sleep deprived. Staying up all night partying is common among college students as going off to college may be the first time the student has had the opportunity to do so and many consider it to be a bonding experience or a way to make friends in a new place. Grabbing a less than stellar meal from the nearest fast food joint or having a pizza delivered is oftentimes a choice that a student makes rather than a necessity. Eating a meal like this is easier than shopping for a meal, cooking a meal, and cleaning up after a meal. Eating on the run may also be what â€Å"all of the other kids are doing† and again it is a way to fit in. Whereas it is true that some students must maintain employment while attending school this may not have to be the stressor that it often is. Time management skills can come in handy when trying to juggle work and school. Taking time to relax is one of the most important and effective ways of reducing stress. This can; however, oftentimes be misconstrued and taken out of context. One of the worst, and most common, pastimes college students use to relax is drinking alcoholic beverages. Binge drinking can be very detrimental to schoolwork as this can do away with a person’s judgment skills, time management skills, and a person’s healthy well-being. Research shows that binge drinking affects approximately 50% of college students (Stunn, n. d. ). Binge drinking can lead to missing classes because the student may be to hung-over to attend or if the student does manage to attend the mind and body may not be functioning at full capacity and may lead to an inability to concentrate and retain information. When this kind of drinking is done night after night it can lead to many absences or missed assignments, which can compound a student’s stress level by having to make up the work or complete the work in a shorter time with little to no instruction This information would be recommended to others in the class because as students stress will be an important factor during not only college years but also in future years as well. It is important that as an individual a person has coping mechanisms to deal with stress to maintain a healthy lifestyle. Research done on the topic of how stress can negatively affect a student’s GPA is important in learning how to better deal with the stressors in one’s life to overcome barriers and achieve the goals he or she has set. Enrolling in college is a big step in which nobody intentionally sets up to fail. Whereas there are many changes that a college student must adapt to there are an equal number of services both on campus and off that will help a student overcome the barriers to effective learning and to become a better student despite the changes in life. Learning ways to manage time, learning to make choices that will facilitate not only a healthy relationship with peers but also a healthy lifestyle, and learning to cope with the sometimes daily changes in life is part of growing up and moving into the adult world.

Literature Review Behavioural Responses of Student...

Bullying is a serious occurrence that is plaguing youth all over the globe. Bullying, a form of aggression, can be experienced in four forms: physical, verbal, social or cyber (Oh Hazler, 2009; Trach, Hymel, Waterhouse Neale, 2010). However, all bullying is composed of three specific concepts—causing their victims harm, possessing greater power then their victims and repetition (Oh Hazler, 2009). Read into the definition of â€Å"bullying† and one would simply identify a bully and a victim yet they would likely fail to identify a key influence: bystanders. It is their impact on bullying that can create serious problems therefore understanding the bystander’s role is vital in trying to decrease the occurrence of bullying (Oh Hazler,†¦show more content†¦Conversely, defenders are the individuals who intervene and use anti-bullying or prosocial behaviour, meaning that they voluntarily act in ways that benefit others (Oh Hazler, 2009;Thornberg, 2007). Trach, Hymel, Waterhouse and Neale (2010) and Thornberg (2007) recall statistics that suggest bystanders use 54% of their time to reinforce the bully by passively watching, 21% to actively encourage the bully and only 25% to intervene and defend the bully. It is important to understand these categories because they help further understand the influence of these bystanders and their reasoning for their behaviours. Although all of the research is interested in bystander behaviour, the approach of the researcher seems to differ in that they are either interested in predictors of behaviour or the reasoning behind bystander behaviour. Predictors such as gender, grade, past experiences with bullying, type of bullying witnessed and friendship dynamics have displayed some significant trends (Oh Hazler, 2009; Trach, Hymel, Waterhouse and Neale, 2010). For example, researchers identify strong and consistent trends that indicate girls are more likely to support victims with positive actions w hile boys were more likely to report doing nothing (Oh Hazler, 2009; Trach, Hymel, Waterhouse and Neale, 2010). Furthermore, older students were far more passive or aggressive in actions while younger students were more willing to takeShow MoreRelatedLiterature Review: Behavioural Responses of Student Bystanders in Situations of Bullying970 Words   |  4 PagesBullying, a form of aggression, can be experienced in several forms: physical, verbal, social or cyber. All bullying is composed of three specific concepts—causing their victims harm, possessing greater power than their victims and repetition (Oh Hazler, 2009). Most often it is just the bully and a victim taken into consideration yet this fails to identify a key influence: bystanders. It is their impact on bullying that creates serious problems thus understanding the bystander’s role is vitalRead MoreThe Impact Of Self Esteem On The Relationship Between Empathy And Cyberbullying7843 Words   |  32 Pages a nd denigration (Best, Manktelow, Taylor, 2014). Cyberbullying has moved bullying from beyond the traditional school yard harassment into the home, and into the once safe domain of an adolescent’s bedroom. Thus, for many cybervictims this often means there is little or no escape from the harassment, abuse, and denigration. The purpose of the current literature review is twofold: (a) to provide a narrative review of the research on cyberbullying among adolescents, including definitions, prevalence