To improve the segmentation quality and efficiency of color image,a novel approach which combines the advantages of the mean shift(MS) segmentation and improved ant clustering method is proposed.The regions which can ...To improve the segmentation quality and efficiency of color image,a novel approach which combines the advantages of the mean shift(MS) segmentation and improved ant clustering method is proposed.The regions which can preserve the discontinuity characteristics of an image are segmented by MS algorithm,and then they are represented by a graph in which every region is represented by a node.In order to solve the graph partition problem,an improved ant clustering algorithm,called similarity carrying ant model(SCAM-ant),is proposed,in which a new similarity calculation method is given.Using SCAM-ant,the maximum number of items that each ant can carry will increase,the clustering time will be effectively reduced,and globally optimized clustering can also be realized.Because the graph is not based on the pixels of original image but on the segmentation result of MS algorithm,the computational complexity is greatly reduced.Experiments show that the proposed method can realize color image segmentation efficiently,and compared with the conventional methods based on the image pixels,it improves the image segmentation quality and the anti-interference ability.展开更多
An improved approach for J-value segmentation （JSEG） is presented for unsupervised color image segmentation. Instead of color quantization algorithm, an automatic classification method based on adaptive mean shift ...An improved approach for J-value segmentation （JSEG） is presented for unsupervised color image segmentation. Instead of color quantization algorithm, an automatic classification method based on adaptive mean shift （AMS） based clustering is used for nonparametric clustering of image data set. The clustering results are used to construct Gaussian mixture modelling （GMM） of image data for the calculation of soft J value. The region growing algorithm used in JSEG is then applied in segmenting the image based on the multiscale soft J-images. Experiments show that the synergism of JSEG and the soft classification based on AMS based clustering and GMM overcomes the limitations of JSEG successfully and is more robust.展开更多
茶毫是红茶外形品质的重要评价指标,当前主要依赖于专业人员的感官评价,主观性强且评语抽象,缺乏客观化、数字化的品质评价手段。为构建茶毫品质数字化评价方法,采集3个不同茶毫品质等级的祁门红茶样品图像,采用HSV彩色图像分割技术对...茶毫是红茶外形品质的重要评价指标,当前主要依赖于专业人员的感官评价,主观性强且评语抽象,缺乏客观化、数字化的品质评价手段。为构建茶毫品质数字化评价方法,采集3个不同茶毫品质等级的祁门红茶样品图像,采用HSV彩色图像分割技术对感兴趣区域(Region of interest,ROI)提取HSV颜色空间分量特征,构建分割指数(Segmentation index,SI)检索得到茶毫、茶身和阴影的最佳分割阈值,采用掩膜法和像素点判别对图像分割效果进行定性和定量评价,并构建茶毫比例量化方法。结果表明,茶毫、茶身和阴影区域的平均分割准确率达到了98.70%,进一步通过茶毫比例量化结果获得祁门红茶3个茶毫品质等级(“显毫”“多毫”和“少毫”)的推荐毫量比例阈值。不同毫量梯度拼配茶样的线性回归分析(R2=0.958,P<0.01)及滇红、金骏眉的泛化应用效果表明,构建的茶毫品质数字化评价方法在不同毫量区间和不同红茶类别上具有较好的适应性。展开更多
基金Project(60874070) supported by the National Natural Science Foundation of China
文摘To improve the segmentation quality and efficiency of color image,a novel approach which combines the advantages of the mean shift(MS) segmentation and improved ant clustering method is proposed.The regions which can preserve the discontinuity characteristics of an image are segmented by MS algorithm,and then they are represented by a graph in which every region is represented by a node.In order to solve the graph partition problem,an improved ant clustering algorithm,called similarity carrying ant model(SCAM-ant),is proposed,in which a new similarity calculation method is given.Using SCAM-ant,the maximum number of items that each ant can carry will increase,the clustering time will be effectively reduced,and globally optimized clustering can also be realized.Because the graph is not based on the pixels of original image but on the segmentation result of MS algorithm,the computational complexity is greatly reduced.Experiments show that the proposed method can realize color image segmentation efficiently,and compared with the conventional methods based on the image pixels,it improves the image segmentation quality and the anti-interference ability.
文摘An improved approach for J-value segmentation （JSEG） is presented for unsupervised color image segmentation. Instead of color quantization algorithm, an automatic classification method based on adaptive mean shift （AMS） based clustering is used for nonparametric clustering of image data set. The clustering results are used to construct Gaussian mixture modelling （GMM） of image data for the calculation of soft J value. The region growing algorithm used in JSEG is then applied in segmenting the image based on the multiscale soft J-images. Experiments show that the synergism of JSEG and the soft classification based on AMS based clustering and GMM overcomes the limitations of JSEG successfully and is more robust.
文摘茶毫是红茶外形品质的重要评价指标,当前主要依赖于专业人员的感官评价,主观性强且评语抽象,缺乏客观化、数字化的品质评价手段。为构建茶毫品质数字化评价方法,采集3个不同茶毫品质等级的祁门红茶样品图像,采用HSV彩色图像分割技术对感兴趣区域(Region of interest,ROI)提取HSV颜色空间分量特征,构建分割指数(Segmentation index,SI)检索得到茶毫、茶身和阴影的最佳分割阈值,采用掩膜法和像素点判别对图像分割效果进行定性和定量评价,并构建茶毫比例量化方法。结果表明,茶毫、茶身和阴影区域的平均分割准确率达到了98.70%,进一步通过茶毫比例量化结果获得祁门红茶3个茶毫品质等级(“显毫”“多毫”和“少毫”)的推荐毫量比例阈值。不同毫量梯度拼配茶样的线性回归分析(R2=0.958,P<0.01)及滇红、金骏眉的泛化应用效果表明,构建的茶毫品质数字化评价方法在不同毫量区间和不同红茶类别上具有较好的适应性。
