Image processing and It’s forensic significance

Image processing and It’s forensic significance

1. Image processing and It’s forensic significance Submitted By: Submitted To: Ritu BalA DEPARTMENT OF ZOOLOGY, M .Sc. Forensic S ci.(F) Kurukshetra University Roll no.19

2. Contents: 1. I ntroduction 2 . H istory 3. I mage processing 4. Steps of image processing 5. Forensic analysis in dip 6. Forensic significance of image processing 7. Conclusion References

3. Introduction Image : A binary representation of some visual information. Image an array of multiple pixels. I t is defined by the mathematical function f (x, y) where x and y are the two co-ordinates horizontally and vertically. the value of f (x, y) at any point is gives the pixel value at that point of an image.

4. Type of image Type of image on basic of coloured components : Binary image Black and white image Greyscale image Coloured image On the basic of signal used : Analog image Digital image

5. History of image processing E arly 1920s: One of the first applications of digital imaging was in the newspaper industry - The Bartlane cable picture transmission service – images were transferred by submarine cable between London and new York – pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer. M id to late 1920s: Improvements to the Bartlane system resulted in higher quality images – new reproduction processes based on photographic techniques – increased number of tones in reproduced images.

6. 1960s: Improvements in computing technology and the onset of the space race led to a huge work in digital image processing – 1964: Computers used to improve the quality of images of the moon taken by the ranger 7 probe – such techniques were used in other space missions including the apollo landings . 1980s - Today: the use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas – image enhancement/restoration , artistic effects –,medical visualization , industrial inspection , law enforcement ,human computer interface.

7. IMAGE PROCESSING It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Two types method used in image processing : Analog image processing : It is referred to the alteration of image through electrical means such example is the television image. The television signal is a voltage level which varies in amplitude to represent brightness through the image. Digital image processing : It processing is referred to processing of a two -dimensional picture by a digital computer it implies digital processing of any two-dimensional data. A digital image is an array of actual numbers represented by a finite number of bits.

8. Digital image processing Digital image processing focuses on two major tasks: Improvement of pictorial information for human interpretation Processing of image data for storage, transmission and representation A dvantage of digital image processing methods is its versatility, repeatability and the preservation of original data precision.

9. Fundamental steps of digital image processing:

10. Step 1. image acquisition : The image is captured by a sensor ( eg. camera), and digitized if the output of the camera or sensor is not already in digital form, using analogue-to-digital convertor

11. Step 2. image enhancement: The process of manipulating an image so that the result is more suitable than the original for specific applications. The idea behind enhancement techniques is to bring out details that are hidden, or simple to highlight certain features of interest in an image.

12. step 3.Image restoration Improving the appearance of an image - tend to be mathematical or probabilistic models. Enhancement, on the other hand, is based on human subjective preferences regarding what constitutes a “good” enhancement result

13. Step 4. colour image processing Use the colour of the image to extract features of interest in an image T here are two types of colour sensors. one illuminates the object with broad wavelength light and differentiates the three types of colour in the receiver. The other type illuminates the object with the three types of light (red, blue, and green) independently.

14. Step 5. wavelets and multiresolution process Wavelets are the foundation of representing images in various degrees of resolution. it is used for image data compression. M ultiresolution images can also be applied to 1d signals, very useful for – image compression (e.g., in the jpg-2000 standard) and removing noise.

15. Step 6. image compression I mage compression is a process applied to a graphics file to minimize its size in bytes without degrading image quality below an acceptable threshold. Techniques for reducing the storage required to save an image or the bandwidth required to transmit it. E xamples include  TIFF ,GIF, and PNG .

16. Step 7. morphological processing: Morphological image processing pursues the goals of removing these imperfections by accounting for the form and structure of the image. Morphological filters are used to sharpen images. D ilation and erosion Tools for extracting image components that are useful in the representation and description of shape. In this step, there would be a transition from processes that output images, to processes that output image attributes.

17. Step8. image segmentation Segmentation procedures partition an image into its constituent parts or objects. H elps in reducing the complexity of the image to make further processing or analysis of the image simpler

18. Step9. representation description and recognition A problem domain is coded into an image processing system in the form of a knowledge database. Representation -follows the output of a segmentation stage. Boundary representation: focus on external shape characteristics, such as corners and inflections - region representation: focus on internal properties, such as texture or skeleton shape. Description: also called, feature selection, deals with extracting attributes that result in some information of interest. Recognition: the process that assigns label to an object based on the information provided by its description.

19. Forensic analysis of image processing: Different type of editing operators applicable to image :

20. Example of forgery done with geomatic modification: Scale : change in image content size Rotation: change in image content ordination Reflect: flip over image content Translate : change image content position

21. example of forgery done with Enhancement : It includes color correction, correcting image blur, reducing image noise, skin texture improvement, mask removal, background enhancement, adjustment to brightness and contrast, and many more. Computer-assisted image analysis will help forensic specialists and officials in getting suitable conclusions for investigation. Image composition : p rocess includes geometric transformation to generate artifacts in image histograms as a useful clue for composite forgery detection as rotation, scaling, and translation are involved to make the image more realistic.

22. Example of forgery done with content modification: Image cloning : U sing multiple images for hiding some content or emphasizing important objects as forged regions are similar to well-matched components like-color, noise, texture, transition-curves and lines, size, etc. Image splicing : C reating a forged image by trimming certain objects from an image and by adding them to some other image

23. Software used in analysis of image processing : Software's : commonly used : paint , photoshop , lightroom, light wave 3-D Analysis by using different languages program such as python Other online program : foto forensic , forensically etc.

24. Photoshop Editing software

25. Basic features of photoshop : Layers: content layer and adjustment layer Pen tool : used for drawing paths along with the anchor points, the creative scope it provides is limitless. Colour channel : contains colour information , two types of model RBG and CYMK.

26. Slice tool : I t helps users to slice up a big image or artwork into smaller sections that fit together like a jigsaw P rovides the feature to snip the images into slices. Hue and saturation : To adjust or change richness of colour and intensity of photo. For example, cadmium orange is a high saturation color, and burnt sienna is a low saturation color.

27. Shapes : g raphic shapes in the form of a filled layer with a vector mask, a solid fill, or as a path outline for example rectangular , rounded rectangular , polygon, custom shapes etc. Selection tools: marquee tool generally have oval and square shapes as a selection tool. Categories as object ,quick and magic selection tool. Vector mask : resolution independent object created with pen and shape tool with an anchor point Related to density , feathers

28. Retouching tool : M odifying the arrangement of pixels in an image to remove imperfections from the image stamp tool, pattern stamp tool, healing tool, spot healing tool, patch tool, redeye tool, and much more 3-D: A series of images related to the 3d object and facial expressions from the animation within photoshop .

29. File formats supported by photoshop JPEG (joint photographic expert group): for digital photos PNG (portable network graphics):   for saving digital photos as high-quality originals. GIF (graphics interchange format):  gif allows you to create simple animations. PDF (portable document format):  for viewing, sharing, and printing the documents. TIFF (tagged image file format):  standard for images destined for commercial printing. PSD (photoshop document):  working file in photoshop.

30. Advantages of photoshop Photoshop is available on multiple platforms. Features of editing different types of image format. Professional color grading support. Advanced layer management. Professional plug-ins, filters, textures, and overlays. Merging images and graphics. Supports video clips and animation layers. Disadvantages of photoshop Beginners may find the interface complicated to learn. It is a bit expensive. Untested beta versions are sometimes released and may cause the software to crash. A progress monitoring facility is not available in few tools. Less support for vector graphics design.

31. Forensic significance of image processing : Forensic image processing aims to secure digital communication like online transactions for surveillance support, CCTV recording, bank data tempering, road accident scenes, etc. Digital image analysis includes image recovery and surveillance for image information improvement. The goal of forgery detection is to maximize the extraction of information from manipulated images, particularly noisy and post-processed images. detection of images is still having computational complexity in terms of time and space especially in small tampered regions where statistical measurement analysis for image integrity becomes difficult due to similar components used in forged regions.

32. Forgery In the present work, an analysis of image processing for forensic investigation is proposed with the help of programming tools. Datasets of tampered images are collected from online resources for the testing procedure. Forgery detection of tampered images is evaluated based on various parameters for artifact removal and is compared with recent existing techniques. Image forgery detection algorithm is developed for providing quality of services like security, accuracy, reliability, computational complexity, and real-time implementation .

33. Conclusion: Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. Digital image analysis includes image recovery and surveillance for image information improvement. It becomes impossible to trust the content of the images in the digital world because digital image quality will be degraded during the compression, transmission, capturing, archiving, and retrieving process. Digital image processing is becoming popular with many advantages in scientific and engineering applications, the forgery techniques are also growing at a rapid rate.

34. References Hanji R. B. and Rajpurohit V. S. (2013) Forensic Image Analysis - A Frame work. The International Journal of forensic computer science 1: 13-19 Monica and Passi A (2020) Image processing for forensic investigation; Manav Rachna international university, Shodhganga@INFLIBNET http://hdl.handle.net/10603/324267 Woods R. E. and Gromzalez R. C. (2009) Digital image processing, 2 nd edition, Prentice hall Upper Saddle River, New Jersey 07458 (779pp.) https://www.geeksforgeeks.org/what-is-photoshop

35. This Photo by Unknown Author is licensed under CC BY-NC