In this paper, we propose a fast full-search block matching algorithm for motion estimation, based on binary edge information. The binary edge information allows a faster search by reducing the computational complexity. It also reduces error, which is generated by the block located on the boundary of moving objects. After we transform the input image into an edge-based image using Sobel masks, we convert the result into a binary edge image using median-cut quantization. We then perform block matching using the binary edge image. If there exists blocks such that the error of the binary block matching exceeds threshold, we only perform edge intensity-based block matching within those blocks. We improve computational efficiency by eliminating an unnecessary searching process in no-motion regions. Simulation results have shown that the proposed method reduces the computational complexity and provides similar PSNR performance to the Full Search Block Matching Algorithm (FS-BMA)