Digital Signal Processing (DSP) is widely used in various industrial fields and military equipment fields. OpenCV is a common open source image processing algorithm library. However, there are few implementations for OpenCV transplantation and optimization on DSP platforms. In this paper, OpenCV is successfully transplanted on a TMS320C6678 DSP platform and generates an underlying support library with most functions preserved. Based on this, we deeply analyze the computational features and data flow of some OpenCV library functions running on this platform. As a result, an optimization method for these OpenCV library functions is proposed. This method combines DMA, Cache operations and OpenMP parallel frameworks, which are supported by TI 6678 architecture. According to this method, we implement the optimization and multi-core parallelism for a class of OpenCV library functions on the TI 6678 chip. With the help of our method, the optimized OpenCV library function running on a single core of TI 6678 chip can be speeded up by up to 3.6 times. On this basis, we parallelize this class of library functions on 8 cores, obtaining the speedup of 2.55 to 7.06.