{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,24]],"date-time":"2023-01-24T09:17:04Z","timestamp":1674551824923},"reference-count":26,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,1]]},"abstract":"<p>Images from digital imaging devices are prevalent in society. The signatures of these images can be extracted as sensor pattern noise (SPN) and classified according to their source devices. In this paper, the authors assess the reliability of an unsupervised classifier for forensic investigation of digital images recovered from storage devices and to identify the best position for cropping the images before processing. Cross validation was performed on the classifier to assess the error rate and determine the effect of the size of the sample space and the classifier trainer on the performance of the classifier. Moreover, the authors find that the effect of saturation and subsequently the contamination of the SPN in the images affected performance negatively. To alleviate the negative performance, the authors identify the areas of images where less contamination occurs to perform cropping.<\/p>","DOI":"10.4018\/jdcf.2011010101","type":"journal-article","created":{"date-parts":[[2013,10,21]],"date-time":"2013-10-21T12:29:10Z","timestamp":1382358550000},"page":"1-13","source":"Crossref","is-referenced-by-count":3,"title":["On the Performance of Li\u2019s Unsupervised Image Classifier and the Optimal Cropping Position of Images for Forensic Investigations"],"prefix":"10.4018","volume":"3","author":[{"given":"Ahmad Ryad","family":"Soobhany","sequence":"first","affiliation":[{"name":"Keele University and Forensic Pathways Ltd., UK"}]},{"given":"Richard","family":"Leary","sequence":"additional","affiliation":[{"name":"Forensic Pathways Ltd., UK"}]},{"given":"KP","family":"Lam","sequence":"additional","affiliation":[{"name":"Keele University, UK"}]}],"member":"2432","reference":[{"key":"jdcf.2011010101-0","doi-asserted-by":"crossref","unstructured":"Alles, E. J., Geradts, Z. J. M. H., & Veenman, C. J. (2008). Source camera identification for low resolution heavily compressed images. In Proceedings of the International Conference on Computational Sciences and Its Applications (pp. 557-567).","DOI":"10.1109\/ICCSA.2008.18"},{"key":"jdcf.2011010101-1","doi-asserted-by":"publisher","DOI":"10.4018\/jdcf.2010040102"},{"key":"jdcf.2011010101-2","first-page":"69","article-title":"Source camera identification based on CFA interpolation. In","volume":"3","author":"S.Bayram","year":"2005","journal-title":"Proceedings of the IEEE International Conference on Image Processing"},{"key":"jdcf.2011010101-3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1183"},{"key":"jdcf.2011010101-4","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2008.926993"},{"key":"jdcf.2011010101-5","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2007.916285"},{"key":"jdcf.2011010101-6","author":"B.Efron","year":"1997","journal-title":"An introduction to the bootstrap"},{"key":"jdcf.2011010101-7","unstructured":"Farid, H. (2006). Digital Image Ballistics from JPEG Quantization (Tech. Rep. No. TR2006-583). Hanover, NH: Dartmouth College."},{"key":"jdcf.2011010101-8","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2008.931078"},{"key":"jdcf.2011010101-9","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2005.1407714"},{"key":"jdcf.2011010101-10","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","author":"T.Hastie","year":"2009","journal-title":"The elements of statistical learning: Data mining, inference, and prediction"},{"issue":"5","key":"jdcf.2011010101-11","first-page":"475","article-title":"Digital camera identification: A brief test of a method based on the sensor noise.","volume":"59","author":"T.Hoglund","year":"2009","journal-title":"Journal of Forensic Identification"},{"key":"jdcf.2011010101-12","doi-asserted-by":"crossref","unstructured":"Hsu, Y. F., & Chang, S. F. (2007). Image splicing detection using camera response function consistency and automatic segmentation. In Proceedings of the IEEE International Conference on Multimedia and Expo (pp. 28-31).","DOI":"10.1109\/ICME.2007.4284578"},{"key":"jdcf.2011010101-13","unstructured":"Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (Vol. 2, pp. 1137-1145)."},{"issue":"2","key":"jdcf.2011010101-14","first-page":"7","article-title":"Source camera identification using enhanced sensor pattern noise.","volume":"5","author":"C.-T.Li","year":"2010","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"jdcf.2011010101-15","doi-asserted-by":"crossref","unstructured":"Li, C.-T. (2010). Unsupervised classification of digital images using enhanced sensor pattern noise. In Proceedings of the IEEE International Symposium on Circuits and Systems (pp. 3429- 343).","DOI":"10.1109\/ISCAS.2010.5537850"},{"key":"jdcf.2011010101-16","first-page":"938","article-title":"Radiometric calibration from a single image. In","volume":"2","author":"S.Lin","year":"2004","journal-title":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition"},{"key":"jdcf.2011010101-17","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2006.873602"},{"key":"jdcf.2011010101-18","first-page":"3253","article-title":"Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising. In","volume":"6","author":"M. K.Mihcak","year":"1999","journal-title":"Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing"},{"key":"jdcf.2011010101-19","doi-asserted-by":"crossref","unstructured":"Ng, T.-T., Chang, S.-F., & Tsui, M.-P. (2007). Using geometry invariants for camera response function estimation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1-8).","DOI":"10.1109\/CVPR.2007.383000"},{"key":"jdcf.2011010101-20","first-page":"172","article-title":"Source camera identification using footprints from lens aberration. In Digital Photography II","volume":"6069","author":"K.San Choi","year":"2006","journal-title":"Proceedings of the Society for Photo-Instrumentation Engineers"},{"key":"jdcf.2011010101-21","author":"H. T.Sencar","year":"2007","journal-title":"Overview of state-of-the-art in digital image forensics"},{"key":"jdcf.2011010101-22","doi-asserted-by":"publisher","DOI":"10.4018\/jdcf.2009040102"},{"key":"jdcf.2011010101-23","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2006.890307"},{"key":"jdcf.2011010101-24","doi-asserted-by":"crossref","unstructured":"Van, L. T., Emmanuel, S., & Kankanhalli, M. S. (2007). Identifying source cell phone using chromatic aberration. In Proceedings of the IEEE International Conference on Multimedia and Expo (pp. 883-886).","DOI":"10.1109\/ICME.2007.4284792"},{"key":"jdcf.2011010101-25","author":"A.Webb","year":"1999","journal-title":"Statistical pattern recognition"}],"container-title":["International Journal of Digital Crime and Forensics"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=52775","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T18:02:04Z","timestamp":1654106524000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jdcf.2011010101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2011,1,1]]},"references-count":26,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2011,1]]}},"URL":"https:\/\/doi.org\/10.4018\/jdcf.2011010101","relation":{},"ISSN":["1941-6210","1941-6229"],"issn-type":[{"value":"1941-6210","type":"print"},{"value":"1941-6229","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,1,1]]}}}