Recognition of hand-written ballot symbols is crucial in vote-counting system based on image understanding. To improve the accuracy of ballot symbol recognition, a symbol recognition approach based on run feature was proposed. Firstly, the concept of run was presented and a discriminant model was established based on run features of ballot symbols. Secondly, the relative positions of runs were described with a ternary tree. In addition, the main run regions were extracted in noisy environment by merging run regions, and an approach of recognizing ambiguous symbols was also given. Finally, the experimental results show that the run features can accurately reflect the geometrical features of ballot symbols. The proposed approach achieves high accuracy, and its accuracy is 6.07% higher than that of template matching algorithm.

Efficient Graph-Based algorithm is a novel image segmentation method based on graph theory and it can segment an image at an extraordinary speed. However, it is easily influenced by the threshold value and the segmentation result is imprecise when dealing with the border and texture. Here, an improved algorithm is proposed, which has three main contributions: 1) RGB color space is replaced by Lab color space; 2) Laplacian operator is used to divide the edges of weighted graph into border edges and non-border edges, and those non-border edges are given priority; 3) the optimum threshold is evaluated based on uniformity measurement. Experimental results show that the improved algorithm is more accurate and adaptive than traditional Graph-based algorithms, and segmentation results are closer to human vision property.

The security of E-commerce determines its development; however, traditional means of security certification cannot meet the demand on reliability. To ensure the security in E-commerce communication, a new method of security certification was proposed based on rolled fingerprint reconstruction and digital signature. Firstly, the image sequence of rolling fingerprints was reconstructed into a high-quality complete fingerprint image, and then the features were extracted as the key of digital signature. Thirdly, the message embedded with digital signature was transferred. At the same time, the correctness and completeness of the message were checked, and the validity of the sender was also identified. The experimental results show that the proposed algorithm can be used for rolling fingerprint reconstruction in any direction to get a high-quality fingerprint image. And it can run in real-time because of low complexity. The rolling fingerprint, as the security certification medium, ensures the security of E-commerce.

Evolving new software component based on previous software components is a key technique to improve software reusability and satisfy users' various demands. In this paper, an interactive evolution model was proposed based on multiple Agents, which could autonomously process consistent data. Then, the aspect weaving mechanism, which can effectively reduce the coupling degree of different function areas, was introduced in evolution to insert new codes into the exact places of target component. Furthermore, the evolution complexity was also discussed and several indicators and a model were given to calculate evolution cost. Finally, a data exchange component used in digital campus system was given to illustrate the effectiveness of above evolution methods.