利用人工智能技术对二维图像进行分类

G. Perelmuter, Paula Pereira, M. Vellasco, M. Pacheco, E. Carrera
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引用次数: 1

摘要

本文提出了一个由三个模块组成的“智能分类器”的结构:1)预处理模块,负责对原始图像进行变换;2)特征提取器,由遗传算法实现,负责选择最相关的系数;3)分类器,由神经网络实现。通用算法已被用作大型数据集和神经网络的搜索技术,由于它们能够从复杂的数据集中提取信息,已被广泛应用于计算机视觉的模式分类。完整的图像分类系统不受被分析对象的平移、旋转和大小的影响。
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Classification of bidimensional images using artificial intelligence techniques
This article presents the structure of an "intelligent classifier" composed of three modules: 1) the preprocessor, responsible for the transformation of the raw image; 2) the characteristics extractor, implemented by a genetic algorithm, which is responsible for the selection of the most relevant coefficients; and 3) the classifier, implemented by a neural network. Generic algorithms have been used as a search technique for large sets of data and neural networks, due to their ability to extract information from complex sets of data, have been largely applied in computer vision for pattern classification. The complete image classification system is invariant to translation rotation and sizing of the analysed object.
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