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A FPGA-based canny algorithm threshold acquisition method and device
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An acquisition method and threshold technology, applied in the field of image processing, can solve the problems of large storage and calculation, difficult FPGA, slow speed, etc., and achieve the effect of fast acquisition, speed and precision
Active Publication Date: 2021-06-01
FORYOU GENERAL ELECTRONICS
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However, in the key threshold calculation, due to the need to process the entire image data, the amount of storage and calculation is huge, and FPGA is difficult to adapt to. Therefore, in the prior art, the acquisition of CANNY algorithm threshold is obtained by PC or AMR processor operation. , and then passed to the FPGA
This method is slow, can only adapt to static images, and cannot meet the processing requirements of video
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Embodiment 1
[0034] Such as figure 1 As shown, the present embodiment provides a FPGA-based CANNY algorithm threshold acquisition method, including:
[0035] Pre-step: Grayscale the original video frame, perform Gaussian filtering on the grayscaled video frame, and calculate the gradient magnitude of the grayscaled video frame.
[0036] These steps are prior art and will not be repeated here.
[0037] The gradient magnitude in the step of calculating the gradient magnitude of the grayscaled video frame is used as the gradient input of the method.
[0038] Step 1. Calculate the gradient maximum value and average value of the video frame to be processed.
[0039] In this embodiment, the maximum value of the gradient is found through the comparator, and the average value of the gradient is calculated through the accumulator and the divider.
[0040] For example, in this embodiment, the gradient maximum value G max =169, gradient average G av =44.
[0041] Step 2. Determine the segmentat...
Embodiment 2
[0062] Such as image 3 As shown, the present embodiment provides a FPGA-based CANNY algorithm threshold acquisition device, including a gradient input module, a gradient processing module, a pixel processing module, and a system threshold calculation module;
[0063] The gradient input module is used to input the video gradient information calculated by the system;
[0064] The gradient processing module is used to process the input video gradient information to generate a gradient interval;
[0065] The pixel processing module is used to process the pixels in each gradient interval to obtain the number of pixels with the largest jump;
[0066] The system threshold calculation module is configured to determine the system threshold according to the number of pixels with the largest jump obtained by the pixel processing module.
[0067] In this embodiment, the gradient processing module includes: a gradient average calculation unit for calculating the gradient average calcula...
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Abstract
The present invention provides a CANNY algorithm threshold acquisition method and device based on FPGA. The method includes: calculating the gradient maximum value and average value of video frames to be processed; determining the segmentation step size and the total number of segmentations to obtain gradient intervals; counting the number of pixels in all gradient intervals; Compare whether the difference between the number of pixels in adjacent gradient intervals exceeds the preset range, and if so, mark the smaller number of pixels in the adjacent gradient intervals as the number of suspected threshold pixels; obtain the number of pixels with the largest jump among the number of suspected threshold pixels; Calculate the system threshold according to the number of pixels with the largest jump; use the final threshold to perform edge detection. The invention realizes the rapid acquisition of the CANNY algorithm threshold.
Description
technical field [0001] The invention relates to the technical field of image processing, in particular to an FPGA-based method and device for acquiring a CANNY algorithm threshold. Background technique [0002] In image processing technology, the edge of an image refers to the part where the brightness of the local area of the image changes significantly. The gray profile of this area can generally be regarded as a step, that is, a sharp change from a gray value in a small buffer area. to another grayscale value with a large difference in grayscale. The edge part of the image concentrates most of the information of the image. The determination and extraction of the image edge is very important for the recognition and understanding of the entire image scene. measurement, detection and localization. [0003] Canny edge detection algorithm is an edge detection algorithm based on image gradient calculation developed by John F.Canny in 1986. It is a standard algorithm for edg...
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