Copy-Move Detection in Optical Microscopy: A Segmentation Network and a Dataset

• Published in: IEEE signal processing letters Vol. 32; pp. 1106 - 1110
• Main Authors: Shao, Hao-Chiang, Liao, Yuan-Rong, Tseng, Tse-Yu, Chuo, Yen-Liang, Lin, Fong-Yi
• Format: Journal Article
• Language: English
• Published: New York IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: attention; co-saliency; Copy-move forgery detection; Correlation; Datasets; Decoding; Encoders-Decoders; Feature extraction; Forgery; Fraud; Image segmentation; Microscopy; multiresolution; Object recognition; Optical imaging; Optical microscopy; optical microscopy images; Tensors

With increasing revelations of academic fraud, detecting forged experimental images in the biomedical field has become a public concern. The challenge lies in the fact that copy-move targets can include background tissue, small foreground objects, or both, which may be out of the training domain and...