Canny edge detector

Overview

The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images, see [1]. The following table shows an example input image, a set of input parameters for the canny edge detector algorithm (explained below), and the corresponding edge image.

Input	Parameters	Output
	\begin{align*} \mathit{normType} &= VPI\_NORM\_L2 \\ \mathit{gradMethod} &= GEN\_GRADIENT\_SOBEL \\ \mathit{gradientSize} &= 3 \\ \mathit{edgeValue} &= 255 \\ \mathit{nonEdgeValue} &= 0 \\ \mathit{thresholdStrong} &= 300 \\ \mathit{thresholdWeak} &= 100 \end{align*}

Implementation

Canny edge detector is a multi-stage algorithm:

1. Noise reduction
   Since edge detection is easily affected by noise, a Gaussian filter is applied to the image first.
2. Find the intensity and angle of each pixel in the image
   The smoothed image from stage 1 is then filtered with edge detection filters in both horizontal and vertical direction, resulting in \(G_x\) and \(G_y\). The intensity and angle of each pixel is calculated as follows:

   \begin{align*} Intensity &= \sqrt{G_x^2 + G_y^2} \\ Angle &= arctan(\frac{G_y}{G_x}) \end{align*}

   The gradient direction is always perpendicular to edges. It is rounded to one of four angles representing vertical, horizontal and two diagonal directions.
3. Thin the edge by non-maximum suppression
   For each pixel in the image, check if the intensity is a local maximum in the gradient direction. If it is, keep it as edge pixel, otherwise remove it as non-edge pixel.
4. Double thresholding
   Two thresholding values are provided and they are called strong threshold and weak threshold. For each pixel, if the intensity is greater than the strong threshold, then it is marked as strong edge. If the intensity is less than the weak threshold, then it is marked as non-edge. Any intensity value in between of the strong threshold and weak threshold is marked as weak edge.
5. Track edge by hysteresis
   If the weak edge is connected to a strong edge, then this weak edge is changed into a strong edge. Repeat this process until all the weak edges that are connected to strong edges are found. Mark the rest of weak edges as non-edge.

C API functions

For list of limitations, constraints and backends that implements the algorithm, consult reference documentation of the following functions:

Function	Description
vpiCreateCannyEdgeDetector	Creates payload for vpiSubmitCannyEdgeDetector.
vpiInitCannyEdgeDetectorParams	Initialize vpiInitCannyEdgeDetectorParams with default values.
vpiSubmitCannyEdgeDetector	Runs the canny edge detector algorithm over an image.

Usage

Language: C/C++ Python

1. Import VPI module

   import vpi

2. Run canny edge detector on input image using the CUDA backend and the given kernel. Input and output are VPI images.

   with vpi.Backend.CUDA:
       output = input.canny(thresh_strong=300, thresh_weak=100, edge_value=255, nonedge_value=0, norm=vpi.Norm.L2)

1. Initialization phase
   1. Include the header that defines the canny edge detector algorithm functions and parameter structure.

      #include <vpi/algo/CannyEdges.h>

   2. Define the input image object.

          VPIImage input = /*...*/;

   3. Create the output image object.

          int32_t w, h;
          vpiImageGetSize(input, &w, &h);
       
          VPIImage output;
          vpiImageCreate(w, h, VPI_IMAGE_FORMAT_U8, 0, &output);

   4. Create the stream where the algorithm will be submitted for execution.

          VPIStream stream;
          vpiStreamCreate(0, &stream);

   5. Create a payload for the canny edge detector algorithm that will perform the correction.

          int width, height;
          vpiImageGetSize(input, &width, &height);
       
          VPIPayload payload;
          vpiCreateCannyEdgeDetector(VPI_BACKEND_CUDA, width, height, &payload);

2. Processing phase
   1. Initialize the parameter structure with user-provided parameters. In this example, the parameters are set to reflect the output above,

          VPICannyEdgeDetectorParams params;
          vpiInitCannyEdgeDetectorParams(&params);

   2. Submit the algorithm and its parameters to the stream.

          float thresholdStrong = 300;
          float thresholdWeak = 100;
          float edgeValue = 255;
          float nonEdgeValue = 0;
          VPI_CHECK_STATUS(vpiSubmitCannyEdgeDetector(stream, VPI_BACKEND_CUDA, payload, input, output, thresholdStrong,
                                                          thresholdWeak, edgeValue, nonEdgeValue, &params));

   3. Optionally, wait until the processing is done.

          vpiStreamSync(stream);

3. Cleanup phase
   1. Free resources held by the stream, the input image and the output image.

          vpiStreamDestroy(stream);
          vpiImageDestroy(input);
          vpiImageDestroy(output);

For more information, see Canny Edge Detector in the "C API Reference" section of VPI - Vision Programming Interface.

Performance

Performance benchmarks will be added at a later time.

References

1. https://en.wikipedia.org/wiki/Canny_edge_detector