现今,互联网主要围绕人工智能、大数据、虚拟现实等展开,这些都是当今的热词,是大势所趋,而图像识别技术就是人工智能的一个重要领域。OpenCV是一个跨平台的计算机视觉库。它用于各种图像和视频分析,如面部识别和检测,车牌阅读,照片编辑...现今,互联网主要围绕人工智能、大数据、虚拟现实等展开,这些都是当今的热词,是大势所趋,而图像识别技术就是人工智能的一个重要领域。OpenCV是一个跨平台的计算机视觉库。它用于各种图像和视频分析,如面部识别和检测,车牌阅读,照片编辑,高级机器人视觉,光学字符识别等等。文章对基于开源计算机视觉库OpenCV,实现在开发平台vistual studio 2017下利用OpenCV进行猫脸检测和定位及使用感知哈希算法实现猫脸相似图片的搜索。展开更多
Citrus anthracnose is a common fungal disease in citrus-growing areas in China,which causes very serious damage.At present,the manual management method is time-consuming and labor-consuming,which reduces the control e...Citrus anthracnose is a common fungal disease in citrus-growing areas in China,which causes very serious damage.At present,the manual management method is time-consuming and labor-consuming,which reduces the control effect of citrus anthracnose.Therefore,by designing and running the image retrieval system of citrus anthracnose,the automatic recognition and analysis of citrus anthracnose control were realized,and the control effect of citrus anthracnose was improved.In this paper,based on the self-collected and collated citrus anthracnose image database,we use three image features to realize an image retrieval system based on citrus anthracnose through SMV,AP clustering optimization.The results show that:1)In the accuracy of image feature retrieval,Gist feature extraction>cumulative color histogram>Gabor texture feature;2)In the maximum divergence diversity retrieval,semi-supervised AP clustering retrieval>AP clustering retrieval>SVM relevance feedback results>initial retrieval.3)Practice shows that this technology can reduce the workload of monitoring and management in the control process of citrus planting area,and promote the intelligent and efficient control of citrus anthracnose,which has high practical application value.展开更多
文摘现今,互联网主要围绕人工智能、大数据、虚拟现实等展开,这些都是当今的热词,是大势所趋,而图像识别技术就是人工智能的一个重要领域。OpenCV是一个跨平台的计算机视觉库。它用于各种图像和视频分析,如面部识别和检测,车牌阅读,照片编辑,高级机器人视觉,光学字符识别等等。文章对基于开源计算机视觉库OpenCV,实现在开发平台vistual studio 2017下利用OpenCV进行猫脸检测和定位及使用感知哈希算法实现猫脸相似图片的搜索。
基金supported in part by the National Natural Science Foundation of China under Grant 61772561in part by the Key Research and Development Plan of Hunan Province under Grant 2018NK2012+2 种基金in part by the Science Research Projects of Hunan Provincial Education Department under Grant 18A174in part by the Degree&Postgraduate Education Reform Project of Hunan Province under Grant 209and in part by the Postgraduate Education and Teaching Reform Project of Central South University of Forestry&Technology under Grant 2019JG013.
文摘Citrus anthracnose is a common fungal disease in citrus-growing areas in China,which causes very serious damage.At present,the manual management method is time-consuming and labor-consuming,which reduces the control effect of citrus anthracnose.Therefore,by designing and running the image retrieval system of citrus anthracnose,the automatic recognition and analysis of citrus anthracnose control were realized,and the control effect of citrus anthracnose was improved.In this paper,based on the self-collected and collated citrus anthracnose image database,we use three image features to realize an image retrieval system based on citrus anthracnose through SMV,AP clustering optimization.The results show that:1)In the accuracy of image feature retrieval,Gist feature extraction>cumulative color histogram>Gabor texture feature;2)In the maximum divergence diversity retrieval,semi-supervised AP clustering retrieval>AP clustering retrieval>SVM relevance feedback results>initial retrieval.3)Practice shows that this technology can reduce the workload of monitoring and management in the control process of citrus planting area,and promote the intelligent and efficient control of citrus anthracnose,which has high practical application value.
