In this paper, we consider a natural paradigm for lifting of crisp-set binary filters to fuzzy filters for hardware implementation and process the gray-scale realizations of binary images as [0,1]-valued fuzzy binary images. We present the implementation of the filtering algorithms for smoothing, peak detection and edge detection of such fuzzy images using the Xilinx Virtex series of FPGA for real-time processing of image sequences. The erosion filter forms the core for all of the filtering algorithms and the dilation filter itself is implemented as a function of the erosion filter. Smoothing is achieved using fuzzy opening of the input image using the user defined fuzzy structuring element. A fuzzy top-hat transform is used for peak detection. As opposed to gray-scale top-hat, which detects only the narrow peaks, the fuzzy top-hat is shown to detect both the narrow as well as wide peaks within the same image. Edge detection algorithm uses the fuzzy morphological gradient wherein the set minus operation has been performed between the dilated and the eroded images. Pipelined architectures are used for the erosion filter design and the use of flops has been maximized to achieve a high clock rate. The throughput measurements and the results generated by the implemented filters are also presented.