A SpatioSpectral Hybrid Convolutional Architecture for Hyperspectral Document Authentication Hyperspectral Document Image (HSDI) analysis allows for efficient and accurate differentiation of inks with visually similar color but unique spectral response, which is a crucial step in authentication of documents. Various HSDI based ink discrimination methods are available in the current literature, however, more accurate and robust methods are required to empower document authentication. Contrary to the former ink mismatch detection methods based on spectral features only, we present a novel method based on deep learning that exploits the spectral correlation as well as the spatial context to enhance ink mismatch detection. Spectral responses of the target pixel and its neighboring pixels are organized in an image format and fed to a Convolutional Neural Network (CNN) for classification. The proposed method achieves the highest accuracy among the other ink mismatch detection methods on the UWA Writing Ink Hyperspectral Images database (WIHSI), which demonstrates the effectiveness of deep learning models employing spatiospectral hybrid features for document authentication. Detailed experimental analysis for selection of appropriate CNN architecture, spatiospectral data format and training ratio is presented along with a comparison with the previous methods on this subject.

Characters Verification via Siamese Convolutional Neural Network In the printing and carving industries, it is necessary to check whether printed outputs or carved wares are missing or etched through comparing the drawings. Traditional approaches and identification methods canxe2x80x99t be used for this application where the number of character categories are not determined, and where the character may be unique designed by manufacturer. Driven by the onetoone matching pattern, we propose an endtoend dual input network for automatic comparison, which uses convolutional neural network to extract features from the scanned images which collected from printed matters. Then, we convert the corresponding drawing to the vector of the same dimension to calculate distance and the matchmismatch result. Experiments show that our method can effectively solve the problem of character comparison with many types, and at the same time propose an automated comparing program for the industrial imprinting process.