Real-time medical vision systems using single system on chip (SoC) can be employed for early diagnosis of melanoma. This paper presents, a basic border detection algorithm developed based on ZYNQ-7000 SoC, using VIVADO High Level Synthesis (HLS) tool. We take the advantage of accelerating an embedded system design on a single SoC, which offers the required features for real-time processing of skin cancer images. Our ultimate aim is to develop novel methods to detect melanoma more accurately and faster and implement the algorithms on portable vision systems for medical imaging applications with high resolution and performance. Different edge detection approaches such as Sobel, Kirsch, Canny and LoG have been implemented on ZYNQ-7000 for border detection of skin lesions, which can be used in early diagnosis of melanoma. The results show that the extended 5×5 canny edge detection algorithm implemented on the proposed embedded platform has better performance in comparison with other reported methods. The performance evaluation of this approach has shown good processing time of 60 fps for real time applications.