کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6941474 | 1450112 | 2018 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Locating splicing forgery by fully convolutional networks and conditional random field
ترجمه فارسی عنوان
محل تقلب تقلبها با استفاده از شبکه های کاملا مجزا و فیلد تصادفی شرطی
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کلمات کلیدی
جعل جعل، شبکه عصبی عمیق شبکه کاملا متقارن، زمینه تصادفی محض،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
To expose and locate splicing forgery, hand-crafted features are often utilized to discern tampered area in a synthesized image. However, given a spliced picture without prior knowledge, it is difficult to tell which feature will be effective to expose forgery. In addition, a certain hand-crafted feature can only handle one kind of splicing forgery. To address these issues, a method based on using deep neural networks and conditional random field is proposed in this paper. It is achieved by training three different fully convolutional networks (FCNs) and a condition random field (CRF). Each FCN is specialized to deal with different scales of image contents. CRF adaptively combines detection results from these neural networks. Then the trained FCNs-CRF can be used to perform image authentication, yielding pixel-to-pixel forgery prediction. Our FCNs-CRF framework achieves improved performance comparing to existing methods relying on hand-crafted features.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 66, August 2018, Pages 103-112
Journal: Signal Processing: Image Communication - Volume 66, August 2018, Pages 103-112
نویسندگان
Bo Liu, Chi-Man Pun,