Vision Processing with the Canny Edge Detection Reference Design

ID 683433
Date 2/14/2015
Document Table of Contents

1.4.2. Gaussian Blurring

Canny edge detection is very sensitive to noise. The design uses a two dimensional Gaussian filter to blur the grayscale output image

A Gaussian filter is a low pass filter that attenuates high frequency noise. By convolving the image matrix with the Gaussian kernel, the design smudges the image as each individual output pixel is the weighted Gaussian average of its surrounding pixels (spatial weighted averaging). To obtain the discrete Gaussian kernel coefficients, the design determines the kernel size and chooses the appropriate standard deviation from the continuous 2D Gaussian equation. Implementing 2D convolution in hardware is similar to that of 1D convolution. Both cases use a tapped delay line. However the 2D case needs to delay an entire video line to access the previous matrix row entry using FIFO buffers. For previous column entries, the design uses register delay lines. Hence, a FIFO buffer implements row delays; registers implement column delays.

Figure 3. Gaussian Blurring

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