针对传统彩色图像分割中出现的单纯利用颜色空间，只考虑图像的全局分布，或是只考虑图像的局部区域和边缘信息等问题，提出了一种基于Fuzzy ART模型的层次化彩色图像分割算法。该算法有效地利用图像的亮度空间分布、细节信息以及颜色空间信息，对图像进行分级特征提取，利用Fuzzy ART模型基于人类视觉特性的稳定、快速的在线学习和记忆能力，对图像进行层次化的区域划分，形成对图像的分层表达方式，从而达到良好的分割效果；将其与FFCM算法进行比较，取得了较好的结果。

Aiming at the problems in the color space information, the global distribution and the local regions and edges information of an image are considered separately appearing in traditional color image segmentation, a hierarchical color image segmentation algorithm based on Fuzzy ART model is proposed. The algorithm frame mainly involves the effective utilization of the luminance distribution, the edge information and the color space information. A set of hierarchical features are extracted from the image, and making use of the ability of stable and fast incremental learning and memorizing of Fuzzy ART model, the image is partitioned into several regions hierarchically and the hierarchical representation of the image is formed. According to the hierarchical representation of the image, good segmentation results can be obtained. Compared with the FFCM algorithm, better results can also be obtained.