Task mapping has been a hot topic in MPSoC software design for decades. During the mapping process, load balance and communication optimization have been two important performance optimization factors. This paper studies the relations between load balance, inter-processor communications and communication pipeline technique during the mapping process, and proposes an Integer Linear Programming (ILP)-based static task mapping approach, which considers both load balance and communication optimization. The approach consists of an optimized ILP model for task mapping with fewer variables compared to previous ILP mapping works. Moreover, to enhance the scalability of the ILP task mapping, the Task-Processor-Cluster (TP-CLUSTER) algorithm is proposed to reduce the scale of the task graph and the number of processors and then solve the coarse-grained input by the ILP mapping. To increase the adaptability of the ILP task mapping, the improved augmented ε-constraint (AUGMECON2) method is further integrated with the ILP formulations to select the best mapping for different applications. Experimental results on a 2/4/8/16/24-CPU platform of both synthetic and real-life benchmarks demonstrate the efficiency of the proposed approach.

Digital watermarking technology is an effective method for copyright protection of digital information, such as images, documents, etc. In this paper, we propose a high capacity text image watermarking technique against printing and scanning processes. Firstly, this method obtains the invariant in the process of printing and scanning under the mathematical hypothesis model of print-scan transformation. Then based on the print-scan invariant, the Fourier descriptor is used to flip the trivial pixel points with high frequency information on the character boundary. Next, considering the resolution of the print-scan equipment and its influence on the print-scan invariant, a quadratic quantization function is proposed to embed watermark information of multiple bits for a single character. Finally, the QR code (Quick Response code) is researched, which has large information capacity, robust error correction ability and high decoding reliability. By using the QR code as the watermark information, we can reduce the impact of bit error rate during watermark extraction, and the robustness of the watermark information can be improved. The experimental results show that the proposed text watermarking algorithm has the advantages of anti-print scanning, anti-scaling, large capacity and good visual effects.

Document skew detection is one of the key technologies in most of the document analysis systems. However, existing skew detection methods either have low accuracy or require a large amount of computation. To achieve a good tradeoff between efficiency and performance, we propose a novel skew detection approach based on bounding boxes, probability model, and Dixon’s Q test. Firstly, bounding boxes are used to pick out the eligible connected components (ECC). Then, we calculate the slopes of the skew document with the probability model. Finally, we find the optimal result with Dixon’s Q test and projection profile method. Moreover, the proposed method can detect the skew angle in a wider range. The experimental results show that our skew detection algorithm can achieve high speed and accuracy simultaneously compared with existing algorithms.