文章使用FN—SOM网进行图像分割,它是SOM网的一种改进形式,通过引入虚假邻域的概念来增强SOM网的聚类特性。首先定义每个像素的特征向量,并且以此作为网络的输入向量进行图像的初步分割;再对初次分割后的图像进行融合:最后获得符合要求的分割图像。文中把FN—SOM网络的分割结果和传统的SOM网进行了验证比较,获得了较为理想的实验效果。
Image segmentation plays an important role in image processing. In this paper, a method for segmenting images based on SOM neural network is proposed. At first, the pixels are clustered based on their color and spatial features, where the clustering process is accomplished with a FN - SOM network. Then, the clustered blocks are merged to a specific number of regions. In conclusion, we demonstrate the efficiency of the application with contrast and analysis.