Description: This algorithm will perform hough transform and detect shape of an object.-This algorithm will perform hough transfo rm and detect shape of an object. Platform: |
Size: 4284276 |
Author:Kent |
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Description: This algorithm will perform hough transform and detect shape of an object.-This algorithm will perform hough transfo rm and detect shape of an object. Platform: |
Size: 4284416 |
Author:Kent |
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Description: object recognition using fast adaptive hough transform 快速自适应霍夫变换
作者：D.D. Haule. A.S. Malowany
Computer Vision and Robotics Laboratory
Department of Electrical Engineering
McGill University。IEEE 1989的文章，对指导霍夫变换检测目标的识别有一定的参考意义-object recognition using fast adaptive hough transform Express Adaptive Hough Transform Author: DD Haule. AS Malowany Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University. The IEEE 1989 article in guiding Hough Transform Detect target recognition must have reference significance Platform: |
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Author:miaosiyi |
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Description: 本文提出了一种基于方向可变滤波器的改进Hough变换方法。该方法首先利用方向可变滤波器检测出图像边缘以及边缘的方向特性，然后基于边缘点及其方向，通过改进的Hough变换得到圆心、半径。最后，将该算法应用于球类对象分割并得到较好的结果。-In this paper, a variable filter based on the direction of improving the method of Hough transform. The direction of the first to use this method to detect variable edge filter, as well as the direction of the edge characteristics, and then based on the edge points and their direction, by improving the center of the Hough transform, radius. Finally, the object segmentation algorithm is applied to ball games and get better results. Platform: |
Size: 761856 |
Author:王浩 |
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Description: hough transform
this project applyes hough transform on given picture in order to be able to calculate object in real world Platform: |
Size: 785408 |
Author:lilou |
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Description: this package include moving object detection and hough transform to recognise parallel line in an image. a sample image included in package for test. Platform: |
Size: 39936 |
Author:meyba92 |
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Description: 包括用C编写的直方图程序，边缘检测程序，不变距程序，灰度变换程序，膨胀腐蚀，物体测量，梯度算子和霍夫变换。-Including the use of C programs written in the histogram, edge detection procedure, unchanged from the procedure, gray-scale transformation procedure, dilation and erosion, object measurement, gradient operator and the Hough transform. Platform: |
Size: 712704 |
Author:kongdeqi |
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Description: matlab环境下的hough变换实现 检测图像中的直线 并将直线标出 适用于检测目标直线边缘 圆柱形物体边缘 飞机机翼 导弹边缘 机场跑道直线 海天交界线 等-hough transform with matlab ,straight line detection in a image and mark it ,it can detect the edge of the target straight edge, cylindrical object edge ,aircraft wing ,missile ,airport runway ,straight Horizon
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Size: 429056 |
Author: |
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Description: SIFT keypoints of objects are first extracted from a set of reference images[4] and stored in a database. An object is recognized in a new image by individually comparing each feature from the new image to this database and finding candidate matching features based on Euclidean distance of their feature vectors. From the full set of matches, subsets of keypoints that agree on the object and its location, scale, and orientation in the new image are identified to filter out good matches. The determination of consistent clusters is performed rapidly by using an efficient hash table implementation of the generalized Hough transform. Platform: |
Size: 700416 |
Author:ahmed |
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Description: 本文提出了一种基于方向可变滤波器的改进Hough变换方法。该方法首先利用方向可变滤波器检测出图像边缘和边缘的方向特性，然后后基于边缘点及其方向，通过改进的Hough变换得到圆心、半径。最后，将该算法应用于球类对象分割并得到较好的结果。 已通过测试。
-In this paper, based on the direction of the variable filter improved Hough transform method. First, using the direction variable filter to detect the directional characteristics of the image edge and the edge, and then based on the edge of the point and its direction after center, radius through improved Hough transform. Finally, the application of the algorithm the ball object segmentation and better results. Has passed the test. Platform: |
Size: 761856 |
Author:门槛 |
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Description: SIFT(Scale Invariant Feature Transform)即尺度不变特征变换，是 D. G.Lowe 在 1999 年提出的一种基于图像局部特征的描述算子，并于 2004年做了完善。SIFT算法是一种基于线性尺度空间，对图像缩放、旋转甚至仿射变换保持不变的局部特征描述算子，因此被广泛地应用于机器人定位、导航和地图生成中。-This paper presents a method for extracting distinctive invariant features from images that can be used
to perform reliable matching between different views of an object or scene. The features are invariant to image scale
and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in
3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also describes an approach to using these features for object recognition. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm,followed by a Hough transform to identify clusters belonging to a single object, and finally performing verification through least-squares solution for consistent pose parameters. This approach to r Platform: |
Size: 742400 |
Author:欣欣 |
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Description: 数字图像处理在人们的生活中无处不存在着它的影子，是非常流行热门的技术之一，可以说它是一种每时每刻都在改变着人类生活的技术。人们对于物体的识别主要针对于物体的外形，图像分割目的是对图像中有意义的特征部分进行提取，所谓有意义的特征包括图像中物体的外形边缘和区域等。本文主要针对其中的一个传统而经典的分割方法Hough变换而展开。Hough变换实现的是一种从图像空间到参数空间的映射关系，具有对抗噪声的鲁棒性以及在图像中的不连续性等优点，通过它构建的参数空间可以容易地对特定形状，如直线、圆等解析曲线进行判断。-Digital image processing is one of the most popular technologies today, and in our daily life everywhere has its shadow. We can say that it is a kind of all in the changing human life technology. The object recognition mainly based on the shape of the object, and image segmentation is to extract meaningful characteristic aspects of the image, the so-called meaningful features including images of objects in the shape of edge and region. This paper is expended by Hough Transform which is a traditional and classic segmentation method. The Hough transform is a mapping from the image space to the parameter space, and it has robustness to noise, as well as in the discontinuities in the image, etc. The specific shape can easily be detected through its parameter space construction, such as straight lines, circles, and other analytical curve. Platform: |
Size: 3503104 |
Author:yanjue |
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Description: 数字图像处理在人们的生活中无处不存在着它的影子，是非常流行热门的技术之一，可以说它是一种每时每刻都在改变着人类生活的技术。人们对于物体的识别主要针对于物体的外形，图像分割目的是对图像中有意义的特征部分进行提取，所谓有意义的特征包括图像中物体的外形边缘和区域等。本文主要针对其中的一个传统而经典的分割方法Hough变换而展开。Hough变换实现的是一种从图像空间到参数空间的映射关系，具有对抗噪声的鲁棒性以及在图像中的不连续性等优点，通过它构建的参数空间可以容易地对特定形状，如直线、圆等解析曲线进行判断。-Digital image processing is one of the most popular technologies today, and in our daily life everywhere has its shadow. We can say that it is a kind of all in the changing human life technology. The object recognition mainly based on the shape of the object, and image segmentation is to extract meaningful characteristic aspects of the image, the so-called meaningful features including images of objects in the shape of edge and region. This paper is expended by Hough Transform which is a traditional and classic segmentation method. The Hough transform is a mapping from the image space to the parameter space, and it has robustness to noise, as well as in the discontinuities in the image, etc. The specific shape can easily be detected through its parameter space construction, such as straight lines, circles, and other analytical curve. Platform: |
Size: 3276800 |
Author:yanjue |
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Description: This paper introduces a new object tracking method
which combines two algorithms working in parallel, and based on
low-level observations (colour and gradient orientation): the Generalised Hough Transform, using a pixel-based description, and
the Particle Filter, using a global description. The object model is
updated by combining information a back-projection map
computed the Generalised Hough Transform, providing
for every pixel the degree to which it may belong to the
object, and the Particle Filter, providing a probability
density on the global object position. The proposed tracker
makes the most of the two algorithms, in terms of robustness to
appearance variation like scaling, rotation, non-rigid deformation
or illumination changes.-This paper introduces a new object tracking method
which combines two algorithms working in parallel, and based on
low-level observations (colour and gradient orientation): the Generalised Hough Transform, using a pixel-based description, and
the Particle Filter, using a global description. The object model is
updated by combining information a back-projection map
computed the Generalised Hough Transform, providing
for every pixel the degree to which it may belong to the
object, and the Particle Filter, providing a probability
density on the global object position. The proposed tracker
makes the most of the two algorithms, in terms of robustness to
appearance variation like scaling, rotation, non-rigid deformation
or illumination changes. Platform: |
Size: 2140160 |
Author:SALEH |
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Search - hough transform object