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An Edge Detection Method Based on Cellular Automata Theory

A cellular automaton and edge detection technology, applied in image data processing, image analysis, image enhancement, etc., can solve the problems of large noise, large amount of calculation, poor image softness, etc., and achieve low noise, less calculation amount, soft edge effect

Active Publication Date: 2021-11-19
GUANGDONG LYRIC ROBOT INTELLIGENT AUTOMATION CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the Canny algorithm is commonly used to detect edges, such as figure 1 and figure 2 as shown, figure 1 for the original image, figure 2 It is an image obtained by using the Canny algorithm to detect the edge of the image. However, the softness of the image obtained by using the Canny algorithm to detect the edge of the image is poor, and the amount of calculation is large, and the noise generated during the processing is also large

Method used

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  • An Edge Detection Method Based on Cellular Automata Theory
  • An Edge Detection Method Based on Cellular Automata Theory
  • An Edge Detection Method Based on Cellular Automata Theory

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Embodiment 1

[0043] Please refer to image 3 , Figure 4 as well as Figure 5 , image 3 It is a schematic flowchart of an edge detection method based on cellular automata theory in Embodiment 1 of the present invention; Figure 4 It is a schematic flow chart of processing a binarized image in Embodiment 1 of the present invention; Figure 5 It is a schematic flowchart of encoding a digitally represented area in Embodiment 1 of the present invention. As shown in the figure, the edge detection method based on cellular automata theory of the present application specifically includes the following steps:

[0044] S1: Acquire the original image;

[0045] S2: Binarize the original image to obtain a binarized image;

[0046] S3: Perform edge feature extraction on the binarized image according to the cellular automata operation rules with intermediate continuous samples to obtain the target image.

[0047] In step S1, an existing method of collecting original images may be used, for exampl...

Embodiment 2

[0084] In this embodiment, an edge detection method based on cellular automata theory is used to detect figure 1 The edges of the original image shown are detected and extracted.

[0085] S1: collect the original image;

[0086] S2: Use the OTSU algorithm to binarize the original image to obtain a binarized image (such as Figure 13 shown);

[0087] S3: According to the rule56 operation rule with intermediate continuous samples, the edge feature extraction is performed on the binarized image to obtain the target image (such as Figure 14 shown).

[0088] Will Figure 14 and figure 2 By comparison, it can be seen that the target image obtained by the edge detection method based on cellular automata theory is softer, with more details and clearer.

[0089] In summary, in one or more embodiments of the present invention, the edge detection method based on the cellular automata theory of the present invention detects the edge of the image to obtain a target image that is so...

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Abstract

The present invention discloses an edge detection method based on cellular automata theory, which includes the following steps: S1: acquire the original image; S2: perform binarization processing on the original image to obtain a binarized image; S21: according to the binarization The energy distribution of the image is divided into regions; S22: digitally represent the region; S23: code the digitally represented region; S231: calculate the selected region to obtain the number of adjacent matrices; S232: select the region represented by a specific number; S3: Perform edge feature extraction on the binarized image according to the cellular automata operation rules with intermediate continuous samples to obtain the target image. Compared with the image measured by the Canny algorithm, the edge detection method based on the cellular automata theory of the present invention detects the image edge, and the target image is softer, the details are clearer, the noise in the processing process is small, and the amount of calculation is relatively small. less.

Description

technical field [0001] The invention relates to the technical field of image edge detection, in particular to an edge detection method based on cellular automata theory. Background technique [0002] As a basic problem in the image field, edge detection can provide help and reference for many traditional technical fields, such as salient object detection, image segmentation and skeleton extraction. At present, the Canny algorithm is commonly used to detect edges, such as figure 1 and figure 2 as shown, figure 1 for the original image, figure 2 It is an image obtained by using the Canny algorithm to detect the edge of the image. However, the softness of the image obtained by using the Canny algorithm to detect the edge of the image is poor, and the amount of calculation is large, and the noise generated during the processing is also large. Contents of the invention [0003] Aiming at the deficiencies in the prior art, the present invention discloses a method of edge d...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/13G06T9/00
CPCG06T9/00G06T2207/10004G06T7/13
Inventor 周俊杰万君社龚亚忠杜兵
Owner GUANGDONG LYRIC ROBOT INTELLIGENT AUTOMATION CO LTD
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