{"title":"Filtering and Reconstruction System for Gray Forensic Images","authors":"Ahd Aljarf, Saad Amin","volume":97,"journal":"International Journal of Information and Communication Engineering","pagesStart":20,"pagesEnd":26,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10000099","abstract":"<p>Images are important source of information used as<br \/>\r\nevidence during any investigation process. Their clarity and accuracy<br \/>\r\nis essential and of the utmost importance for any investigation.<br \/>\r\nImages are vulnerable to losing blocks and having noise added to<br \/>\r\nthem either after alteration or when the image was taken initially,<br \/>\r\ntherefore, having a high performance image processing system and it<br \/>\r\nis implementation is very important in a forensic point of view. This<br \/>\r\npaper focuses on improving the quality of the forensic images.<br \/>\r\nFor different reasons packets that store data can be affected,<br \/>\r\nharmed or even lost because of noise. For example, sending the<br \/>\r\nimage through a wireless channel can cause loss of bits. These types<br \/>\r\nof errors might give difficulties generally for the visual display<br \/>\r\nquality of the forensic images.<br \/>\r\nTwo of the images problems: noise and losing blocks are covered.<br \/>\r\nHowever, information which gets transmitted through any way of<br \/>\r\ncommunication may suffer alteration from its original state or even<br \/>\r\nlose important data due to the channel noise. Therefore, a developed<br \/>\r\nsystem is introduced to improve the quality and clarity of the forensic<br \/>\r\nimages.<\/p>\r\n","references":"[1] S. Umbaugh, \u201cComputer Vision and Image Processing: a practical\r\napproach using CVIP tools\u201d, UK: Prentice Hall PTR, 1998\r\n[2] M. Breeuwsma, \u201cForensic imaging of embedded systems using JTAG\r\n(boundary-scan),\u201d Digital Investigation, vol. 3, pp. 32-42, 2006\r\n[3] D. Venkateshwar, \u201cImplementation and Evaluation of Image Processing\r\nAlgorithm on FPGA,\u201d International Journal of Theoretical and Applied\r\nComputer Sciences Processing, vol. 1, pp. 1-10, 2006\r\n[4] C. Behrenbruch, \u201cImage filtering techniques for medical image postprocessing:\r\nan overview,\u201d The British Journal of Radiology, vol. 77, pp.\r\n2-6, 2004\r\n[5] E. Brooks, and E. Comber, \u201cDigital imaging and image analysis applied\r\nto numerical applications in forensic hair examination,\u201d Journal of\r\nScience and Justice, vol. 51, pp. 28\u201337, 2010\r\n[6] Z. Geradts, \u201cContent Based Information Retrieval in Forensic Image\r\nDatabases,\u201d Unpublished PhD thesis. Netherland: University of Utrecht,\r\n2001\r\n[7] C. Akujuobi, \u201cThe effects of different wavelets on image\r\nreconstruction,\u201dProceedings of the IEEE. Bringing Together Education,\r\nScience and Technology, vol. 55, pp. 5-10, 1996\r\n[8] D. Janecki, \u201cGaussian filters with profile extrapolation,\u201d Precision\r\nEngineering, vol. 35, pp. 602\u2013 606, 2011\r\n[9] J. Rane, J. Remus and G. Sapiro, \"Wavelet-domain reconstruction of lost\r\nblocks in wireless image transmission and packet-switched networks,\" in\r\nProc. ICIP , vol. 1, pp.309-312, 2002\r\n[10] R. Silva, F. Prado and I. Caputo, \u201cThe forensic importance of frontal\r\nsinus radiographs,\u201d Journal of Forensic and Legal Medicine, vol.16,\r\npp.18\u201323, 2008\r\n[11] G. Yang, P. Burgerb, D. Firmin and S. Underwoodad \u201cStructure\r\nadaptive anisotropic image filtering,\u201d Image and Vision Computing, vol.\r\n14, pp. 135- 145, 1996\r\n[12] H. Aziz, \u201cMedical Image Reconstruction Using Wavelet and Multi \u2013\r\nWavelet Algorithms,\u201d Unpublished dissertation. Coventry: Coventry\r\nUniversity, 2010\r\n[13] P. Bauszat, M. Eisemann and M. Magnor, \u201cGuided Image Filtering for\r\nInteractive High-quality Global Illumination,\u201dComputer Graphics\r\nforum, vol. 30, pp.1361-1368, 2011","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 97, 2015"}