基于大数据分析技术的激光图像分类和识别研究

Research on laser image classification and recognition based on big data analysis technology

为了提高激光图像分类效果,针对激光图像大规模特点,设计了基于大数据分析技术的激光图像分类与识别方法。首先确定激光图像的粗糙度、方向度、对比度纹理特征,构成激光图像纹理特征数据场,然后引入Spark并行式支持向量机算法建立图像分类图器,并根据图像分类器实现激光图像类别,最后进行了激光图像分类和识别的仿真对比测试。测试结果表明,所提方法的激光图像的效率与准确度均优对比方法,完全可以满足大规模激光图像分类与识别的实际应用要求。

In order to improve the effect of laser image classification,a laser image classification and recognition method based on large data analysis technology is designed according to large-scale characteristics of laser image.Firstly,the roughness,orientation and contrast texture features of laser image are determined to form the texture feature data field of laser image.Then,the Spark parallel support vector machine algorithm is introduced to establish image classifier.Laser image classification and recognition are realized according to the image classifier.Finally,the simulation comparison of laser image classification and recognition is carried out.The test results show that the efficiency and accuracy of this method are superior to comparison method,and it can fully meet the practical application requirements of large-scale laser image classification and recognition.