IEEE Transactions on Pattern Analysis and Machine Intelligence · 2002 · 91 citations · 19 references
ComputingHistoric PreservationDigital ForensicsPapermakingPrintmakingDocument Image AnalysisDocument PreservationCanny Edge DetectorDocument EnhancementDocument Image EnhancementDocument RestorationForeground RemovalHandwriting RecognitionPrecisionWavelet Analysis
The study aims to restore handwritten archival documents obscured by ink seepage on the reverse side by recovering their contents through a method that matches both sides to map interfering strokes. The method first aligns the two sides of a document to map interfering strokes, then uses wavelet reconstruction to iteratively enhance foreground strokes and smear interference, thereby improving Canny edge detection of the foreground. The technique achieves 84 % precision and 96 % recall in extracting foreground text, demonstrating effective restoration.
This paper addresses a problem of restoring handwritten archival documents by recovering their contents from the interfering handwriting on the reverse side caused by the seeping of ink. We present a novel method that works by first matching both sides of a document such that the interfering strokes are mapped with the corresponding strokes originating from the reverse side. This facilitates the identification of the foreground and interfering strokes. A wavelet reconstruction process then iteratively enhances the foreground strokes and smears the interfering strokes so as to strengthen the discriminating capability of an improved Canny edge detector against the interfering strokes. The method has been shown to restore the documents effectively with average precision and recall rates for foreground text extraction at 84 percent and 96 percent, respectively.
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De-noising by soft-thresholding
David L. Donoho · IEEE Transactions on Information Theory · 1995 · 9.6K citations