模糊聚类局部保存投影在视觉数据特征提取中的应用

Fuzzy Clustering Based on Locality Preserving Projections for Visual Data Feature Extraction

为解决在处理和计算视觉大数据中遇到的速度瓶颈,提出了一种模糊聚类局部保存投影算法用于视觉数据的特征提取应用中。首先,通过某种方法对图像进行分割;接着,将通过统计方法对图像进行特征描述得到相应的视觉数据;然后,通过提出的模糊聚类局部保存投影对视觉数据进行特征提取;最后,通过Ada Boost对提取后的特征进行识别分类。经在国际公开的UCAS-AOD和Flower-102数据集上进行大量实验,经实验对照,结果验证了模糊聚类局部保存投影算法在视觉数据特征提取中的有效性。

In order to solve the speed bottleneck of visual big data processing and computing speed problem,a fuzzy clustering locality preserving projections algorithm is proposed for feature extraction of visual data.Firstly,the image is segmented by some method.Then,the image is characterized by statistical methods to obtain the corresponding visual data.Then,the visual data is extracted by the fuzzy clustering locality preserving projections proposed.Finally,through AdaBoost,the extracted features are identified and classified.Through a large number of experiments on the internationally published UCAS-AOD and Flower-102 datasets,the experimental results verify the effectiveness of the fuzzy clustering locality preserving projections algorithm in visual data feature extraction.