Description: 图像分割是由图像处理到图像分析的关键步骤，涉及到计算机视觉技术的复杂问题。在医学图像方面，许多应用大都依赖于对图像中目标轮廓的准确提取。基于微分算子检测的方法几乎都对噪声较为敏感且不能保证得到连续的边缘，无法用于辨识和分析目标。由Kass提出的基于主动轮廓线的Snake模型[1]，用一个具有一定弹性的封闭曲线，在曲线自身形状约束力和由图像数据计算而来的外部力的共同作用下演化，来逼近目标边界，完成对图像的分割。
GVF snake VC++做的-Image segmentation by image processing to image analysis of the key steps involved in computer vision technology to complex problems. In medical images, many applications largely depends on the target images extracted contour accuracy. Based on the differential operator method of detecting almost all more sensitive to noise and can not guarantee that they will get straight edge, can not be used for target identification and analysis. Kass raised by the active contour based on the Snake model [1], with a certain flexibility of the closed curve in the curve shape their own binding and calculated by the image data from the external force under the joint effect of the evolution of the boundary to approximate the target , completion of the image segmentation. GVF snake VC++ Make the Platform: |
Size: 149504 |
Author:happynp |
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Description: This paper proposes a new method of extracting and tracking
a nonrigid object moving while allowing camera movement. For object
extraction we first detect an object using watershed segmentation
technique and then extract its contour points by approximating the
boundary using the idea of feature point weighting. For object tracking
we take the contour to estimate its motion in the next frame by the
maximum likelihood method. The position of the object is estimated using
a probabilistic Hausdorff measurement while the shape variation is
modelled using a modified active contour model. The proposed method is
highly tolerant to occlusion. Because the tracking result is stable unless
an object is fully occluded during tracking, the proposed method can be
applied to various applications. Platform: |
Size: 2163712 |
Author:sacoura31 |
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Description: 基于动态轮廓模型的虹膜定位.在数字图像中虹膜位置的有效定位是虹膜识别的关键问题。用一种基于主动轮廓线模型的方法定位虹膜的位置，先用灰度投影法检测出瞳孔内的一点作为瞳孔的伪圆心，该圆心只要能落在瞳孔内部即可。然后以该伪圆心为中心，在其周围等角度间隔地取N个点作为初始的snake基准点，按照snake 的运行机制不断进化，直到虹膜的内边界为止。最后，计算进化后的snake形心和snake上的控制点与该形心的距离，取其平均值作为瞳孔的半径，动态轮廓模型的形心作为瞳孔的圆心，即可准确定位出虹膜内边界的位置。实验表明，与常见的定位方法相比，文中的方法速度快、精度高，而且，对瞳孔初始的伪圆心要求不高，鲁棒性更强。-Iris contour model based on dynamic positioning. In the digital image in the position of the iris iris recognition and effective positioning is the key issue. Using a model based on active contour method of positioning the iris position, the first gray projection method used to detect a point within the pupil as a pupil of the pseudo-center of a circle, the center of a circle can be as long as it falls within the pupil. And then the pseudo-center of a circle centered around the angle of its N-point interval to take the snake as the initial reference point, in accordance with operating mechanism evolving snake, until the iris until the inner boundary. Finally, the calculation of the evolution of the snake-shaped after the heart and snake on the control point with the centroid distance, whichever is the average radius of the pupil as a dynamic contour model of the centroid as the center of the pupil can accurately locate out of the iris inner boundary position. Experiments show that, com Platform: |
Size: 287744 |
Author:318 |
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Description: 传统Snake 模型存在的缺点是, 其初始轮廓必须靠近图像中感兴趣目标的真实边缘,否则会得到错误结
果,且由于Snake 模型的非凸性,结果不能进入感兴趣目标的深凹部分,很容易陷入局部极小点. 由此该文提出一
种基于力场分析的主动轮廓模型,详细分析了基于欧氏距离变换的距离势能力场分布,归纳出感兴趣目标上真轮
廓点与假轮廓点的判别标准. 建立了由曲线能量到最终结果的有效方法,避免了Snake 陷入局部极小点. 实验结果
表明,该模型具有较大的捕获区域,能够进入感兴趣目标的深凹部分,准确提取感兴趣目标的轮廓. 与GVFSnake
模型相比, 该模型具有很小的计算量.-The t raditional snake initial contour should be close to the t rue boundary of interested ob2
ject in an image , or else it would converge to the wrong result . Next , active contours have difficulties
progressing into boundary concavities. Moreover , the t raditional snake and it s almost kinds of im2
proved methods are easy to get into local minimum because snake models are non2convex. An active
contour model based on force field analysis , namely FFASnake model , is presented in this paper.
Based on analyzing force dist ribution rules of distance potential force field , a standard is int roduced
here to distinguish the false one f rom contour point s. Platform: |
Size: 325632 |
Author:罗朝辉 |
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Description: 主动轮廓无边界限制，自适应识别边界并分割出目标图像。将其中所有功能打包称为一个自动轮廓系统。-Active Contour no boundary limits, boundaries and identify adaptive segmentation of the target image. All functions which will be called an automatic contour packaged system. Platform: |
Size: 3334144 |
Author:xiaoqin |
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Description: 为了解决测地线活动轮廓模型分割有凹边界的对象时，将可能陷入非理想局部极小的缺点，自适应测地线活动轮廓模型被提出。新的模型可以通过添加在原始模型的加速度项调整曲线基于曲线和图像的梯度的曲率的演变速度。此外，为了消除噪声或伪边缘的影响，新的前处理Sobel算子结合高斯滤波器和测地线活动轮廓模型梯度的计算方法。-In order to solve the shortcoming of Geodesic Active Contour model that would possibly sink into the non-ideal local minimum when segmenting the objects having concave boundary, an adaptive Geodesic Active Contour model was presented. The new model could adjust the evolution speed of curve based on the curvature of curve and gradient of image by adding an acceleration item in the original model. Moreover, in order to eliminate the influence of noise or false edge, a new pre-process Sobel operator combined the Gaussian filter and calculation of gradient of Geodesic Active Contour model is presented. Platform: |
Size: 38912 |
Author:毛巴马 |
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Description: Active contours is a popular technique for image seg-
mentation. However, active contour tend to converge to the
closest local minimum of its energy function and often re-
quires a close boundary initialization. We introduce a new
approach that overcomes the close boundary initialization
problembyreformulatingtheexternalenergyterm. We treat
theactivecontourasameancurveoftheprobabilitydensity Platform: |
Size: 3202048 |
Author:杨松 |
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Description: 无边界活动轮廓模型的CV分割方法，实时性较好。-The CV segmentation method with no boundary active contour model has good real-time performance. Platform: |
Size: 24524800 |
Author:luojian |
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Search - boundary active contour