{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T04:38:19Z","timestamp":1758083899924,"version":"3.44.0"},"publisher-location":"Cham","reference-count":45,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032046260"},{"type":"electronic","value":"9783032046277"}],"license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-04627-7_19","type":"book-chapter","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T02:07:27Z","timestamp":1757988447000},"page":"329-346","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DocForgeNet: Dual Cross-Stream Fusion Network for\u00a0Robust Forgery Detection in\u00a0Scanned Documents"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1416-3220","authenticated-orcid":false,"given":"Nauman","family":"Riaz","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9697-4285","authenticated-orcid":false,"given":"Stefan","family":"Agne","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6100-8255","authenticated-orcid":false,"given":"Andreas","family":"Dengel","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4239-6520","authenticated-orcid":false,"given":"Sheraz","family":"Ahmed","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,16]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Abramova, S., B\u00f6hme, R.: Detecting copy-move forgeries in scanned text documents. In: Media Watermarking, Security, and Forensics (2016). https:\/\/api.semanticscholar.org\/CorpusID:4468868","DOI":"10.2352\/ISSN.2470-1173.2016.8.MWSF-068"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Ahmed, A.G.H., Shafait, F.: Forgery detection based on intrinsic document contents. In: Proceedings of the 11th IAPR International Workshop on Document Analysis Systems (DAS), pp. 252\u2013256. IEEE (2014)","DOI":"10.1109\/DAS.2014.26"},{"key":"19_CR3","unstructured":"Bao, H., Dong, L., Wei, F.: Beit: BERT pre-training of image transformers. CoRR abs\/2106.08254 (2021). https:\/\/arxiv.org\/abs\/2106.08254"},{"issue":"7","key":"19_CR4","doi-asserted-by":"publisher","first-page":"3286","DOI":"10.1109\/TIP.2019.2895466","volume":"28","author":"JH Bappy","year":"2019","unstructured":"Bappy, J.H., Simons, C., Nataraj, L., Manjunath, B.S., Roy-Chowdhury, A.K.: Hybrid LSTM and encoder-decoder architecture for detection of image forgeries. IEEE Trans. Image Process. 28(7), 3286\u20133300 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR5","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/978-3-642-20039-7_26","volume-title":"Intelligent Information and Database Systems","author":"B Bataineh","year":"2011","unstructured":"Bataineh, B., Abdullah, S.N.H.S., Omar, K.: A statistical global feature extraction method for optical font recognition. In: Nguyen, N.T., Kim, C.-G., Janiak, A. (eds.) ACIIDS 2011. LNCS (LNAI), vol. 6591, pp. 257\u2013267. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-20039-7_26"},{"issue":"11","key":"19_CR6","doi-asserted-by":"publisher","first-page":"2691","DOI":"10.1109\/TIFS.2018.2825953","volume":"13","author":"B Bayar","year":"2018","unstructured":"Bayar, B., Stamm, M.C.: Constrained convolutional neural networks: a new approach towards general purpose image manipulation detection. IEEE Trans. Inf. Forensics Secur. 13(11), 2691\u20132706 (2018)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"19_CR7","unstructured":"Berman, M., Blaschko, M.B.: Optimization of the Jaccard index for image segmentation with the Lov\u00e1sz hinge. CoRR abs\/1705.08790 (2017). http:\/\/arxiv.org\/abs\/1705.08790"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Bertrand, R., Terrades, O.R., Gomez-Kr\u00e4mer, P., Franco, P., Ogier, J.M.: A conditional random field model for font forgery detection. In: 2015 13th International Conference on Document Analysis and Recognition (ICDAR), pp. 576\u2013580 (2015). https:\/\/api.semanticscholar.org\/CorpusID:22313406","DOI":"10.1109\/ICDAR.2015.7333827"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"van Beusekom, J., Shafait, F., Breuel, T.M.: Text-line examination for document forgery detection. Int. J. Document Anal. Recogn. (IJDAR) 16, 189\u2013207 (2012). https:\/\/api.semanticscholar.org\/CorpusID:254113860","DOI":"10.1007\/s10032-011-0181-5"},{"key":"19_CR10","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1007\/978-3-031-73414-4_12","volume-title":"ECCV 2024","author":"Z Chen","year":"2025","unstructured":"Chen, Z., et al.: Enhancing tampered text detection through frequency feature fusion and decomposition. In: Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T., Varol, G. (eds.) ECCV 2024, pp. 200\u2013217. Springer, Cham (2025). https:\/\/doi.org\/10.1007\/978-3-031-73414-4_12"},{"issue":"11","key":"19_CR11","doi-asserted-by":"publisher","first-page":"2284","DOI":"10.1109\/TIFS.2015.2455334","volume":"10","author":"D Cozzolino","year":"2015","unstructured":"Cozzolino, D., Poggi, G., Verdoliva, L.: Efficient dense-field copy\u2013move forgery detection. IEEE Trans. Inf. Forensics Secur. 10(11), 2284\u20132297 (2015). https:\/\/doi.org\/10.1109\/TIFS.2015.2455334","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"19_CR12","doi-asserted-by":"publisher","unstructured":"Cozzolino, D., Poggi, G., Verdoliva, L.: Splicebuster: a new blind image splicing detector. In: 2015 IEEE International Workshop on Information Forensics and Security (WIFS), pp.\u00a01\u20136 (2015). https:\/\/doi.org\/10.1109\/WIFS.2015.7368565","DOI":"10.1109\/WIFS.2015.7368565"},{"key":"19_CR13","doi-asserted-by":"publisher","unstructured":"Dong, C., Chen, X., Hu, R., Cao, J., Li, X.: MVSS-net: multi-view multi-scale supervised networks for image manipulation detection. IEEE Trans. Pattern Anal. Mach. Intell. (2022). https:\/\/doi.org\/10.1109\/TPAMI.2022.3180556","DOI":"10.1109\/TPAMI.2022.3180556"},{"key":"19_CR14","unstructured":"Dosovitskiy, A., et al.: An image is worth $$16 \\times 16$$ words: transformers for image recognition at scale. CoRR abs\/2010.11929 (2020). https:\/\/arxiv.org\/abs\/2010.11929"},{"issue":"3","key":"19_CR15","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1109\/TIFS.2012.2190402","volume":"7","author":"J Fridrich","year":"2012","unstructured":"Fridrich, J., Kodovsky, J.: Rich models for steganalysis of digital images. IEEE Trans. Inf. Forensics Secur. 7(3), 868\u2013882 (2012). https:\/\/doi.org\/10.1109\/TIFS.2012.2190402","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Hao, J., Zhang, Z., Yang, S., Xie, D., Pu, S.: TransForensics: image forgery localization with dense self-attention. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 15035\u201315044 (2021)","DOI":"10.1109\/ICCV48922.2021.01478"},{"key":"19_CR17","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR abs\/1512.03385 (2015). http:\/\/arxiv.org\/abs\/1512.03385"},{"key":"19_CR18","unstructured":"Howard, A.G., et al.: Mobilenets: efficient convolutional neural networks for mobile vision applications. CoRR abs\/1704.04861 (2017). http:\/\/arxiv.org\/abs\/1704.04861"},{"key":"19_CR19","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/978-3-031-09037-0_22","volume-title":"Pattern Recognition and Artificial Intelligence","author":"H Joren","year":"2022","unstructured":"Joren, H., Gupta, O., Raviv, D.: Learning document graphs with attention for image manipulation detection. In: El Yacoubi, M., Granger, E., Yuen, P.C., Pal, U., Vincent, N. (eds.) Pattern Recognition and Artificial Intelligence, pp. 263\u2013274. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-09037-0_22"},{"key":"19_CR20","unstructured":"Katharopoulos, A., Vyas, A., Pappas, N., Fleuret, F.: Transformers are RNNs: fast autoregressive transformers with linear attention. CoRR abs\/2006.16236 (2020). https:\/\/arxiv.org\/abs\/2006.16236"},{"key":"19_CR21","unstructured":"Kitaev, N., Kaiser, L., Levskaya, A.: Reformer: the efficient transformer. CoRR abs\/2001.04451 (2020). https:\/\/arxiv.org\/abs\/2001.04451"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Kwon, M.J., Yu, I.J., Nam, S.H., Lee, H.K.: Cat-net: compression artifact tracing network for detection and localization of image splicing. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 375\u2013384 (2021)","DOI":"10.1109\/WACV48630.2021.00042"},{"key":"19_CR23","doi-asserted-by":"publisher","unstructured":"Lampert, C.H., Mei, L., Breuel, T.M.: Printing technique classification for document counterfeit detection. In: 2006 International Conference on Computational Intelligence and Security, vol.\u00a01, pp. 639\u2013644 (2006). https:\/\/doi.org\/10.1109\/ICCIAS.2006.294214","DOI":"10.1109\/ICCIAS.2006.294214"},{"issue":"9","key":"19_CR24","doi-asserted-by":"publisher","first-page":"1821","DOI":"10.1016\/j.sigpro.2009.03.025","volume":"89","author":"W Li","year":"2009","unstructured":"Li, W., Yuan, Y., Yu, N.: Passive detection of doctored JPEG image via block artifact grid extraction. Signal Process. 89(9), 1821\u20131829 (2009)","journal-title":"Signal Process."},{"key":"19_CR25","doi-asserted-by":"publisher","unstructured":"Liu, X., Liu, Y., Chen, J., Liu, X.: PSCC-net: progressive spatio-channel correlation network for image manipulation detection and localization. IEEE Trans. Circuits Syst. Video Technol. 32, 1\u20131 (2022). https:\/\/doi.org\/10.1109\/TCSVT.2022.3189545","DOI":"10.1109\/TCSVT.2022.3189545"},{"key":"19_CR26","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. CoRR abs\/2103.14030 (2021). https:\/\/arxiv.org\/abs\/2103.14030"},{"key":"19_CR27","unstructured":"Loshchilov, I., Hutter, F.: Fixing weight decay regularization in adam. CoRR abs\/1711.05101 (2017). http:\/\/arxiv.org\/abs\/1711.05101"},{"key":"19_CR28","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1007\/978-3-031-41685-9_8","volume-title":"Document Analysis and Recognition","author":"A Maqsood","year":"2023","unstructured":"Maqsood, A., Riaz, N., Ul-Hasan, A., Shafait, F.: A unified architecture for Urdu printed and handwritten text recognition. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds.) ICDAR 2023, pp. 116\u2013130. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-41685-9_8"},{"key":"19_CR29","doi-asserted-by":"crossref","unstructured":"Mikkilineni, A.K., Chiang, P.J., Ali, G.N., Chiu, G.T.C., Allebach, J.P., Delp, E.J.: Printer identification based on graylevel co-occurrence features for security and forensic applications. In: IS &T\/SPIE Electronic Imaging (2005). https:\/\/api.semanticscholar.org\/CorpusID:13441570","DOI":"10.1117\/12.593796"},{"key":"19_CR30","doi-asserted-by":"publisher","first-page":"2160010","DOI":"10.1142\/S0218001421600107","volume":"35","author":"L Nandanwar","year":"2021","unstructured":"Nandanwar, L., et al.: A new method for detecting altered text in document images. Int. J. Pattern Recogn. Artif. Intell. 35, 2160010 (2021). https:\/\/doi.org\/10.1142\/S0218001421600107","journal-title":"Int. J. Pattern Recogn. Artif. Intell."},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Peng, Z., et al.: Conformer: local features coupling global representations for visual recognition (2021). https:\/\/arxiv.org\/abs\/2105.03889","DOI":"10.1109\/ICCV48922.2021.00042"},{"key":"19_CR32","unstructured":"Pun, A.K., Javed, M., Doermann, D.S.: A survey on change detection techniques in document images (2023). https:\/\/arxiv.org\/abs\/2307.07691"},{"key":"19_CR33","doi-asserted-by":"crossref","unstructured":"Qu, C., et al.: Towards robust tampered text detection in document image: new dataset and new solution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5937\u20135946 (2023)","DOI":"10.1109\/CVPR52729.2023.00575"},{"key":"19_CR34","unstructured":"Ren, S., He, K., Girshick, R.B., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. CoRR abs\/1506.01497 (2015). http:\/\/arxiv.org\/abs\/1506.01497"},{"key":"19_CR35","doi-asserted-by":"publisher","unstructured":"Riaz, N., Arbab, H., Maqsood, A., Nasir, K., Ul-Hasan, A., Shafait, F.: Convtransformer architecture for unconstrained off-line Urdu handwriting recognition. Int. J. Doc. Anal. Recogn. 25(4), 373\u2013384 (2022). https:\/\/doi.org\/10.1007\/s10032-022-00416-5","DOI":"10.1007\/s10032-022-00416-5"},{"key":"19_CR36","doi-asserted-by":"publisher","unstructured":"Riaz, N., Latif, S., Latif, R.: From transformers to reformers. In: 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2), pp.\u00a01\u20136 (2021). https:\/\/doi.org\/10.1109\/ICoDT252288.2021.9441516","DOI":"10.1109\/ICoDT252288.2021.9441516"},{"key":"19_CR37","series-title":"IFIP Advances in Information and Communication Technology","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/978-3-642-04155-6_7","volume-title":"Advances in Digital Forensics V","author":"C Schulze","year":"2009","unstructured":"Schulze, C., Schreyer, M., Stahl, A., Breuel, T.: Using DCT features for printing technique and copy detection. In: Peterson, G., Shenoi, S. (eds.) DigitalForensics 2009. IAICT, vol. 306, pp. 95\u2013106. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-04155-6_7"},{"key":"19_CR38","unstructured":"Vaswani, A., et al.: Attention is all you need (2023). https:\/\/arxiv.org\/abs\/1706.03762"},{"key":"19_CR39","unstructured":"Wang, J., et al.: Objectformer for image manipulation detection and localization (2022). https:\/\/arxiv.org\/abs\/2203.14681"},{"key":"19_CR40","doi-asserted-by":"publisher","unstructured":"Wang, Y., Zhang, B., Xie, H., Zhang, Y.: Tampered text detection via RGB and frequency relationship modeling. Chin. J. Netw. Inf. Secur. 8(3), 29 (2022). https:\/\/doi.org\/10.11959\/j.issn.2096-109x.2022035. https:\/\/www.infocomm-journal.com\/cjnis\/EN\/abstract\/article_172502.shtml","DOI":"10.11959\/j.issn.2096-109x.2022035"},{"key":"19_CR41","doi-asserted-by":"publisher","unstructured":"Wu, L., et al.: Editing text in the wild. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 1500\u20131508. Association for Computing Machinery, New York (2019). https:\/\/doi.org\/10.1145\/3343031.3350929","DOI":"10.1145\/3343031.3350929"},{"key":"19_CR42","doi-asserted-by":"crossref","unstructured":"Wu, Y., AbdAlmageed, W., Natarajan, P.: Mantra-net: manipulation tracing network for detection and localization of image forgeries with anomalous features. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.00977"},{"key":"19_CR43","doi-asserted-by":"publisher","first-page":"33313","DOI":"10.1109\/ACCESS.2023.3264014","volume":"11","author":"C Yan","year":"2023","unstructured":"Yan, C., Li, S., Li, H.: TransU2-Net: a hybrid transformer architecture for image splicing forgery detection. IEEE Access 11, 33313\u201333323 (2023)","journal-title":"IEEE Access"},{"key":"19_CR44","doi-asserted-by":"crossref","unstructured":"Zhou, P., Han, X., Morariu, V.I., Davis, L.S.: Learning rich features for image manipulation detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)","DOI":"10.1109\/CVPR.2018.00116"},{"issue":"8","key":"19_CR45","doi-asserted-by":"publisher","first-page":"877","DOI":"10.1109\/34.709616","volume":"20","author":"A Zramdini","year":"1998","unstructured":"Zramdini, A., Ingold, R.: Optical font recognition using typographical features. IEEE Trans. Pattern Anal. Mach. Intell. 20(8), 877\u2013882 (1998). https:\/\/doi.org\/10.1109\/34.709616","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Document Analysis and Recognition \u2013 ICDAR 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-04627-7_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T02:08:01Z","timestamp":1757988481000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-04627-7_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,16]]},"ISBN":["9783032046260","9783032046277"],"references-count":45,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-04627-7_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,9,16]]},"assertion":[{"value":"16 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Document Analysis and Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuhan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icdar2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iapr.org\/icdar2025","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}