为了把手持相机拍摄的多幅文档图像拼接成一幅大的图像，提出了一种基于全局对准模型的文档图像拼接算法。该算法首先通过估计文档图像的消隐点坐标来校正透视失真，使相邻图像的几何关系可以用仿射变换表示；然后采用随机采样方法调整特征点之间的距离，使其尽可能均匀地分布在整个重叠区域内；接着利用所有重叠图像对的局部对准约束通过建立文档图像拼接的全局对准模型来有效地消除误差积累；最后利用二值函数对图像进行剪切，以减小重叠区内的对准误差。实验结果表明，该方法无需事先标定摄像机的内外参数和限制相机的位置，不仅具有较高的对准精度，且可有效地拼接手持相机拍摄的各种文档图像。

This paper presents a global alignment model based image mosaicing method for camera-captured document images, and it can be used to combine multiple overlapping document images into one large image It corrects the perspective distortion with the estimated vanishing points, and there exists only an affine transform between two adjacent images Then, it adjusts the distance of featurepoints to distribute them as evenly as possible in the overlapping regions Thirdly, it uses local alignment constraints of all the overlapping image pairs to construct global alignment model, thus, to eliminate the error accumulation In order to reduce alignment error of overlapping area, a binary weighted function is used to blend the overlapping region of image pairs This method is unique because it does not require the calibration of the internal/external camera parameters in advance and does not restricting the camera position, thus allowing greater flexibility than scanner-based or fixed-camera-based approaches. It can produce a high resolution and accurate full page mosaic from small image patches of a document