The Vascular Calcification Image Segmentation Based on CV Model

2018 ◽  
Author(s):  
Tiechao Jiang ◽  
Xiaoqiang Ji
Keyword(s):  
Image Segmentation ◽  
Vascular Calcification ◽  
Cv Model

A Neuron Image Segmentation Method Based Deep Boltzmann Machine and CV Model

2021 ◽  
pp. 101871
Author(s):  
Fuyun He ◽  
Xiaoming Huang ◽  
Xun Wang ◽  
Senhui Qiu ◽  
F. Jiang ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Boltzmann Machine ◽  
Segmentation Method ◽  
Deep Boltzmann Machine ◽  
Cv Model

A LEVEL-SET METHOD BASED ON GLOBAL AND LOCAL REGIONS FOR IMAGE SEGMENTATION

2012 ◽  
Vol 26 (01) ◽  
pp. 1255004 ◽  
Author(s):  
YU QIAN ZHAO ◽  
XIAO FANG WANG ◽  
FRANK Y. SHIH ◽  
GANG YU
Keyword(s):  
Image Segmentation ◽  
Level Set Method ◽  
Level Set ◽  
Outer Region ◽  
Descent Method ◽  
Gaussian Kernel ◽  
Gradient Descent Method ◽  
Low Contrast ◽  
Global And Local ◽  
Cv Model

This paper presents a new level-set method based on global and local regions for image segmentation. First, the image fitting term of Chan and Vese (CV) model is adapted to detect the image's local information by convolving a Gaussian kernel function. Then, a global term is proposed to detect large gradient amplitude at the outer region. The new energy function consists of both local and global terms, and is minimized by the gradient descent method. Experimental results on both synthetic and real images show that the proposed method can detect objects in inhomogeneous, low-contrast, and noisy images more accurately than the CV model, the local binary fitting model, and the Lankton and Tannenbaum model.

Segmentation of Marine Spill Oil SAR Image Based on Gabor, Krawtchouk Moments and KFCM

2013 ◽  
Vol 760-762 ◽  
pp. 1462-1466 ◽  
Author(s):  
Li Zhu ◽  
Yi Quan Wu ◽  
Jun Yin
Keyword(s):  
Image Segmentation ◽  
Texture Features ◽  
Sar Image ◽  
Segmentation Method ◽  
Threshold Method ◽  
Krawtchouk Moments ◽  
Model Method ◽  
Sar Image Segmentation ◽  
Segmentation Methods ◽  
Cv Model

To further improve the accuracy of SAR image segmentation in the marine spill oil detection, a segmentation method of marine spill oil images based on Gabor, Krawtchouk moments and KFCM is proposed in this paper. Firstly, the marine spill oil image is decomposed by Gabor transform to obtain the texture features of image. Then, the Krawtchouk moments are applied to extract the shape features of image. Finally, the image segmentation is achieved based on KFCM. A large number of experimental results show that, compared with the related segmentation methods such as Tsallis entropy threshold method,CV model method and the method based on Gabor, Krawtchouk moments and FCM, the proposed method can achieve better result.

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