Canny Edge Detection - 2023.2 English

The Canny edge detector finds the edges in an image or video frame. It is one of the most popular algorithms for edge detection. Canny algorithm aims to satisfy three main criteria:

1. Low error rate: A good detection of only existent edges.
2. Good localization: The distance between edge pixels detected and real edge pixels have to be minimized.
3. Minimal response: Only one detector response per edge.

In this algorithm, the noise in the image is reduced first by applying a Gaussian mask. The Gaussian mask used here is the average mask of size 3x3. Thereafter, gradients along x and y directions are computed using the Sobel gradient function. The gradients are used to compute the magnitude and phase of the pixels. The phase is quantized and the pixels are binned accordingly. Non-maximal suppression is applied on the pixels to remove the weaker edges.

Edge tracing is applied on the remaining pixels to draw the edges on the image. In this algorithm, the canny up to non-maximal suppression is in one kernel and the edge linking module is in another kernel. After non-maxima suppression, the output is represented as 2-bit per pixel, Where:

• 00 - represents the background
• 01 - represents the weaker edge
• 11 - represents the strong edge

The output is packed as 8-bit (four 2-bit pixels) in 1 pixel per cycle operation and packed as 16-bit (eight 2-bit pixels) in 8 pixel per cycle operation. For the edge linking module, the input is 64-bit, such 32 pixels of 2-bit are packed into a 64-bit. The edge tracing is applied on the pixels and returns the edges in the image.

API Syntax

The .. rubric:: API Syntax for Canny is:

template<int FILTER_TYPE,int NORM_TYPE,int SRC_T,int DST_T, int ROWS, int COLS,int NPC,int NPC1,bool USE_URAM=false, int XFCVDEPTH_IN_1 = _XFCVDEPTH_DEFAULT, int XFCVDEPTH_OUT_1 = _XFCVDEPTH_DEFAULT>
void Canny(xf::cv::Mat<SRC_T, ROWS, COLS, NPC, XFCVDEPTH_IN_1> & _src_mat,xf::cv::Mat<DST_T, ROWS, COLS, NPC1, XFCVDEPTH_OUT_1> & _dst_mat,unsigned char _lowthreshold,unsigned char _highthreshold)

The .. rubric:: API Syntax for EdgeTracing is:

template<int SRC_T, int DST_T, int ROWS, int COLS,int NPC_SRC,int NPC_DST,bool USE_URAM=false, int depthm = -1>
void EdgeTracing(xf::cv::Mat<SRC_T, ROWS, COLS, NPC_SRC, depthm> & _src,xf::cv::Mat<DST_T, ROWS, COLS, NPC_DST, depthm> & _dst)

Parameter Descriptions

The following table describes the xf::cv::Canny template and function parameters:

The following table describes the EdgeTracing template and function parameters:

Resource Utilization

The following table summarizes the resource utilization of xf::cv::Canny and EdgeTracing in different configurations, generated using Vivado HLS 2019.1 tool for the Xczu9eg-ffvb1156-1-i-es1 FPGA, to process a grayscale HD (1080x1920) image for Filter size is 3.

The following table summarizes the resource utilization of xf::cv::Canny and EdgeTracing in different configurations, generated using Vivado HLS 2019.1 tool for the xczu7ev-ffvc1156-2-e FPGA, to process a grayscale 4K image for Filter size is 3.

Performance Estimate

The following table summarizes the performance of the kernel in different configurations, as generated using Vivado HLS 2019.1 tool for the Xczu9eg-ffvb1156-1-i-es1, to process a grayscale HD (1080x1920) image for L1NORM, filter size is 3 and including the edge linking module.

Deviation from OpenCV

In OpenCV Canny function, the Gaussian blur is not applied as a pre-processing step.