The warp problems usually make the documents being hardly recognized. Specifically, when we copy a page of a thick book or bound document by digital photocopier, the resulted image is usually warped because of the thickness of the document. We focus on this problem and propose a fast method to restore the warped document image in this paper. The text rectangle area of the document is one of the features of a document. The morphological operation is utilized for text rectangle area segmentation. The DLT method is used to compute the mapping relations between the warped document and the non-warped document. In experimental results, the proposed method works on high resolution image very quickly. The warping text and the figures in documents have been restored by the proposed method successfully. This method is efficiency and fast for implementing on the module of digital photocopier.

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The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use.

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