Data-aware platform realization of videotext extraction for content integration

Abstract

A request to simultaneously comprehend the video content of multi-channels has become. Therefore, a content-integration system was designed by extracting and integrating the embedded videotexts with other video content. This system was developed on a dual-core platform. For speeding up videotext extraction on hardware platforms, a data-aware transfer framework was proposed. In this framework, adaptive-size blocks are transferred based on the computing data, and Single instruction multiple data (SIMD) architectures were manipulated to perform parallel data fetch and computation. The evaluation results demonstrated that the extracted videotexts from the informative channel can be integrated with the main-channel content, and the framework can significantly reduce the number of required cycles in the dual-core architecture. The comparison also presented that the performance of the proposed framework is higher than that of other approaches. Therefore, the proposed frameworks help to advance the data transfer in dual-core platforms and to benefit content integration.