基于MLAP算法的艺术审美图像自组织智能分类管理模型研究

Xinxin Wang
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引用次数: 0

摘要

为了解决传统的大规模数字艺术图像组合和处理复杂低效的问题,提出了基于图像空间相似度算法的自组织技术,为艺术图像提供了颜色、图像、空间布局特征、SIFT等相似度算法的视觉特征表示方法。通过对艺术图像的空间布局特征进行计算和建模,进一步验证了特征的空间聚类方法。基于多层最近邻传播聚类方法,对实验图片数据库进行分层聚类,形成图片的分层视图模式。实验结果表明,该方法在艺术图像的处理和应用中具有良好的性能。
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Research on Self-Organizing Intelligent Classification Management Model of Artistic Aesthetic Images Based on MLAP Algorithm
In order to solve the problem of conventional combination and complex and inefficient processing of large-scale digital art images, the self-organization technology based on an image spatial similarity algorithm is provided, and the visual feature representation method of color, image, spatial layout features, SIFT and other similarity algorithms is provided for art images. The spatial clustering method of features is further verified by calculating and modeling the spatial layout features of art images. Based on the multi-layer Nearest Neighbor Propagation clustering method, the experimental picture database is hierarchically clustered to form a hierarchical view mode of pictures. Experiment results show that this method has an excellent performance in the processing and application of art pictures.
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