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Pulse coupled neural network (PCNN) face image segmenting method simulating visual cells to feel field property

A face image and visual cell technology, applied in the field of image processing, can solve the problem that the connection matrix is ​​not directional and cannot strengthen the connection between central neurons and neighboring neurons.

Inactive Publication Date: 2012-09-19
ZHONGBEI UNIV
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Problems solved by technology

However, the connection matrix is ​​not directional, and it cannot strengthen the connection between the central neuron and the neighboring neurons in the specified direction.

Method used

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  • Pulse coupled neural network (PCNN) face image segmenting method simulating visual cells to feel field property
  • Pulse coupled neural network (PCNN) face image segmenting method simulating visual cells to feel field property
  • Pulse coupled neural network (PCNN) face image segmenting method simulating visual cells to feel field property

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Embodiment Construction

[0027] The present invention utilizes the receptive field model to optimize the structure of the connection matrix, and proposes a pulse-coupled neural network model (IG-PCNN) with directionality and scale, which improves the image segmentation ability of neurons. The neuron structure diagram of the IG-PCNN model is as follows figure 2 shown.

[0028] The principle is as follows:

[0029] see figure 2 , in the receptive field composed of a neuron array with a size of K×L centered on the neuron at coordinates (i, j), the pulse-coupled neural network (improved Gabor-pulse coupled neural networks, IG) with receptive field characteristics The working mechanism of a single neuron in the -PCNN) model can be described as:

[0030]

[0031]

[0032] S K × L = S i - ...

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Abstract

The invention relates to a pulse coupled neutral network (PCNN) disabled face image segmenting method simulating visual cells to feel a field property. The method comprises the following steps of feeling a structure of a feedback domain connection matrix in a field model optimized pulse coupled neutral network by visual cells, obtaining a pulse coupled neutral network model with a directionality and scale; adjusting the model parameters according to the characteristics of a disabled face image; and finally inputting the brightness channel information of the disabled face image to the model to produce human visual simulated face segmenting result. As the cell felt field model optimizes the connection matrix, the pulse coupled neutral network has directionality and scale, the correction rate for segmenting is improved, and better robustness for face segmenting under natural lighting is realized. In addition, compared with the other methods, the method provided by the invention has the advantages of good separation degree between different image contents, well kept details of the image, fast segmenting speed and the like.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for segmenting face images of disabled people using a pulse-coupled neural network (IG-PCNN) that simulates the receptive field characteristics of visual cells. Background technique [0002] As the most important external feature of human beings, face image detection and recognition technology has increasingly become a research hotspot in the field of artificial intelligence. It has extremely broad application prospects in national security, public security and civil affairs, financial customs, insurance and other fields. Face detection or recognition (detection is to determine the existence of the face, and determine the position of the face in the image. Recognition is to recognize the face on the basis of detection), it is necessary to segment the face image, which is the first step in image processing The quality of segmentation plays a key role in feature extraction ...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06N3/02
Inventor 杨娜王浩全
Owner ZHONGBEI UNIV
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