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QPSO (quantum-behaved particle swarm optimization) algorithm based image edge detection method

A technology of image edge and detection method, which is applied in the field of image processing and can solve problems such as difficulties

Inactive Publication Date: 2014-12-24
JIANGNAN UNIV
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Problems solved by technology

These classic algorithms can effectively extract the edges in the image to a certain extent, but the values ​​of some parameters need to be determined in the algorithm, and the determination of the optimal values ​​of these parameters is a relatively difficult problem

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  • QPSO (quantum-behaved particle swarm optimization) algorithm based image edge detection method

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Embodiment Construction

[0033] Combine below Figure 1 to Figure 9 The present invention is further described in detail.

[0034] Step 1: Combine four Adaptive Neuro-Fuzzy Inference System (ANFIS) sub-detectors and a post-processing block to form an image edge detector. Before using the detector to detect the edge of the image, manually construct a training image and use QPSO and linear least squares (LSE) to train the four sub-detectors individually to determine the parameters in the system;

[0035] Specific steps are as follows:

[0036] Step A: Each ANFIS sub-detector has four inputs and one output. Artificially construct an original image, add 30% salt and pepper impulse noise to the image to obtain a noise image, and use it as the input training image of each sub-detector. The edge mark image can be obtained from the original image, and as the training image of the expected output of each sub-detector, all groups of training data are obtained from the input training image and the expected out...

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Abstract

The invention relates to a QPSO (quantum-behaved particle swarm optimization) algorithm based image edge detection method. The method includes: forming an image edge detector by four ANFIS (adaptive neuro-fuzzy inference systems) sub-detectors and a postprocessing module; before using the method to perform edge detection on an image, constructing a training image artificially, independently training the four sub-detectors by means of QPSO and a LSE (linear least square method), and determining parameters in a system; when the four sub-detectors are all train, forming the image edge detector by the sub-detectors with the postprocessing module, and detecting the edge of the test image. The image edge detection method has the advantages that even if the test image is polluted by noise, edge information in the image can be extracted effectively without image filter preprocessing.

Description

technical field [0001] The invention relates to an image edge detection method based on a quantum behavior particle swarm optimization (QPSO) algorithm, which belongs to the technical field of image processing. Background technique [0002] Edge detection is the basis of many image processing operations such as image segmentation, object recognition, image registration, image classification, etc., and its detection quality largely determines the effect of these subsequent operations. [0003] Edge detection algorithms solve image segmentation problems by detecting edges that contain distinct regions. Edges are composed of edge pixels, and edge pixels are those pixels with sudden changes in grayscale in the image. Edge detection algorithms generally use the maximum value of the first derivative of the image or the zero-crossing information of the second derivative to provide the basic basis for judging the edge point. Robert operator, Prewitt operator and Sobel operator are...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06T7/00
Inventor 李岳阳罗海驰孙俊
Owner JIANGNAN UNIV
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