An Improved Image Segmentation Algorithm Based on Local Gaussian Distribution Fitting Energy Model
نویسندگان
چکیده
منابع مشابه
Image Segmentation using Gaussian Mixture Model
Abstract: Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we used Gaussian mixture model to the pixels of an image. The parameters of the model were estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image was made by Bayes rule. In fact,...
متن کاملIMAGE SEGMENTATION USING GAUSSIAN MIXTURE MODEL
Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we have learned Gaussian mixture model to the pixels of an image. The parameters of the model have estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image is made by Bayes rule. In fact, ...
متن کاملAn Improved Pixon-Based Approach for Image Segmentation
An improved pixon-based method is proposed in this paper for image segmentation. In thisapproach, a wavelet thresholding technique is initially applied on the image to reduce noise and toslightly smooth the image. This technique causes an image not to be oversegmented when the pixonbasedmethod is used. Indeed, the wavelet thresholding, as a pre-processing step, eliminates theunnecessary details...
متن کاملConvex Image Segmentation Model Based on Local and Global Intensity Fitting Energy and Split Bregman Method
We propose a convex image segmentation model in a variational level set formulation. Both the local information and the global information are taken into consideration to get better segmentation results.We first propose a globally convex energy functional to combine the local and global intensity fitting terms. The proposed energy functional is then modified by adding an edge detector to force ...
متن کاملImage Object Detection Algorithm Based on Improved Gaussian Mixture Model
Aiming at poor adaptability to illumination variation and single learning rate in traditional Gaussian mixture model, an improved moving object detection algorithm based on adaptive Gaussian mixture model is proposed in this paper, so as to achieve the goal of a self-adaptive background updating model. In this paper, we analyze the existed algorithms and put forward the method to make use of co...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: DEStech Transactions on Engineering and Technology Research
سال: 2016
ISSN: 2475-885X
DOI: 10.12783/dtetr/iect2016/3762