基于脉冲发放皮层模型的图像分割方法

The Method of Image Segmentation Based on Spiking Cortical Model

图像分割算法对光照强度的反应较敏感,同一种算法往往很难对不同光照情况下的图像进行有效分割。基于此,提出一种基于脉冲发放皮层模型的图像分割方法。首先选用不同阶段指数函数对漏电积分器的特性近似逼近。其次,根据亮图像与暗图像之间的区别选择不同的衰减函数,使模型对不同亮度图像具有较好的适应性。实验表明该方法能够对不同光照条件下的图像进行有效地分割,同时较好地保留图像的细节信息,与改进的脉冲耦合神经网络、改进的交叉皮层模型以及二维OTSU算法相比,具有较强的鲁棒性。

Image segmentation algorithm is sensitive to intensity of illumination. The different intensity im- ages are not usually segregated availably based on one kind of algorithm, and therefore in this paper a method of image segmentation based on Spiking Cortical Model （SCM） is proposed. Firstly, choosing different stages membership function to approximate characteristics of dynamic thresholding attenuation. Secondly, choosing the different criterion function to suit for different intensity image based on the difference of bright image and dark image. The Experiments show that proposed algorithm could obtain the segmentation result availably and more details information of image. And it has the stronger robustness, which is better than the improved pulse-coupled neural networks.the improved Intersecting Cortical Model （ICM） and two-dimension OTSU.