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中文摘要：
测距图像的特征提取和类别划分是计算机视觉的热点问题之一。以2D测距图像为研究对象,提出了一种加权的模糊聚类算法-wFCA算法来进行特征提取。为了自主确定准确的聚类数目,利用多种有效性索引函数对不同聚类算法的有效性进行计算评估,选取一种适合于测距图像有效性分析的索引函数。同时,为了解决聚类算法中局部最优问题,提出一种改进的IVGA遗传算法。通过相关算法的性能比较,所提方法的有效性均得以验证。
英文摘要：
Feature extraction and classification division of ranging images is a key problem in computer vision. Considering 2D ranging images as research object, a weighted fuzzy clustering algorithm （wFCA） was proposed. To determine the accurate clustering number automatically, many validation index functions were used to estimate the validity of different clustering algorithms so as to select the most appropriate one for ranging images. At the same time, an improved genetic algorithm IVGA was proposed to solve the local optimum of clustering algorithm. By the comparison with other algorithms, the effectiveness of the algorithms is demonstrated.
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