Description: 对两个及两个以上目标提取边缘和特征，并通过边缘画出目标的外接矩形，外界矩形广泛用于目标的识别和跟踪。-two pairs and two more goals and edge extraction features, and painted goal edge through the external rectangular, Rectangular widely used outside the target identification and tracking. Platform: |
Size: 2464 |
Author:zhouaijun |
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Description: Author: David Sedarsky
Summary: MatLab GUI for interface tracking and edge velocity determination
MATLAB Release: R14SP2
Required Products: Image Processing Toolbox
Description: Itrac works on image pairs taken at times T1 and T2, and tracks the motion of features in the images selected using thresholding and edge detection. Two sample image pairs (LIF images of OH in a turbulent flame) are included in the archive. Some of the work that led me to develop Itrac is detailed here: http://www.opticsinfobase.org/abstract.cfm?URI=ol-31-7-906 Platform: |
Size: 1025369 |
Author:Jallon |
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Description: 对两个及两个以上目标提取边缘和特征，并通过边缘画出目标的外接矩形，外界矩形广泛用于目标的识别和跟踪。-two pairs and two more goals and edge extraction features, and painted goal edge through the external rectangular, Rectangular widely used outside the target identification and tracking. Platform: |
Size: 2048 |
Author:zhouaijun |
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Description: Author: David Sedarsky
Summary: MatLab GUI for interface tracking and edge velocity determination
MATLAB Release: R14SP2
Required Products: Image Processing Toolbox
Description: Itrac works on image pairs taken at times T1 and T2, and tracks the motion of features in the images selected using thresholding and edge detection. Two sample image pairs (LIF images of OH in a turbulent flame) are included in the archive. Some of the work that led me to develop Itrac is detailed here: http://www.opticsinfobase.org/abstract.cfm?URI=ol-31-7-906-Author: David Sedarsky Summary: MatLab GUI for interface tracking and edge velocity determination MATLAB Release: R14SP2 Required Products: Image Processing Toolbox Description: Itrac works on image pairs taken at times T1 and T2, and tracks the motion of features in the images selected using thresholding and edge detection. Two sample image pairs (LIF images of OH in a turbulent flame) are included in the archive. Some of the work that led me to develop Itrac is detailed here: http://www.opticsinfobase.org/abstract . cfm? URI = ol-31-7-906 Platform: |
Size: 1025024 |
Author:Jallon |
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Description: VC编程实现图像处理的一些功能：边缘检测、HOUGH变换、轮廓提取、种子填充、轮廓跟踪-VC programming to achieve some of the features of image processing: edge detection, HOUGH transform, contour extraction, seed filling, Contour Tracking Platform: |
Size: 2136064 |
Author:龚正娟 |
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Description: 两篇人脸检测的英文论文，是花钱买的哦，英文描述中是一篇文章的英文摘要！-Face and facial feature detection plays an important role in various applications such as human computer interaction, video surveillance,
face tracking, and face recognition. Efficient face and facial feature detection algorithms are required for applying to those tasks.
This paper presents the algorithms for all types of face images in the presence of several image conditions. There are two main stages. In
the first stage, the faces are detected from an original image by using Canny edge detection and our proposed average face templates.
Second, a proposed neural visual model (NVM) is used to recognize all possibilities of facial feature positions. Input parameters are
obtained from the positions of facial features and the face characteristics that are low sensitive to intensity change. Finally, to improve
the results, image dilation is applied for removing some irrelevant regions. Additionally, the algorithms can be extended to rotational
invariance problem by using Radon tran Platform: |
Size: 3771392 |
Author:刘宋 |
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Description: 一种运用边缘矢量场的图象分割算法得到连续的边缘信息并做跟踪.-This image segmentation utilizes an edge vector field (EVF) within the curve evolution framework by using both color and texture features.
The JSEG segmentation aims to achieve consistent segmentation and tracking results for scenes with arbitrary non-rigid object motion.
Platform: |
Size: 759808 |
Author:dianalee |
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Description: 实现一种结合颜色空间、变换及变形模板的自动唇部定位及唇轮廓提取、跟踪方法首先在空间建立肤色模型进行人脸检测、定位, 并由人脸几何特征进行唇部粗定位然后结合唇色模型进行变换使肤、唇色差别明显化, 提出根据亮度信息对变换结果预处理后用法进行图像分割, 经唇色模型进一步验证后实现唇部精定位再使用变形模板来进行嘴唇轮廓特征提取, 为增强内轮廓定位的鲁棒性, 对经亮度预处理和唇色模型验证得到的口腔区域边缘图进行曲线拟合来实现内轮廓定位最后, 将唇读图像序列中上一帧的唇部定位结果拓展后作为当前帧的预测区域再进行处理来实现唇动跟踪。-To achieve a combination of color space, transform and deformable template automatic lip localization and lip contour extraction, tracking the establishment of the first color model in the space of face detection, location, geometric features of the face by the rough location and then combined with lip lip transformation so that the skin color model, lip color difference visible, presented the results according to the luminance information to transform the image after pretreatment use of segmentation, and further validated by the lip model to achieve precise positioning and then use the deformation of the lip template for lip contour extraction , to enhance the robustness of location within the outline, by the brightness of the pretreatment and the lip model validation by oral Quyu edge map to fit curve to achieve the final positioning within the contour, the lip-reading image sequence in the last frame of the lips After positioning results extend the forecast area as the current frame Platform: |
Size: 970752 |
Author:郭事业 |
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Description: 红外和可见光的匹配跟踪在军事、遥感等领域有着广泛的应用。针对灰度和图像特征存在比较大差异的红外和可见光图像，本文采用了最大互信息算法，结合形态学梯度和小波分解。互信息算法优点在于不需要对多模图像灰度间的关系做任何假设，不足之处在于它对图像空间信息的忽略而且计算时间较长。本文互信息结合多结构元的形态学梯度检测的图像边缘，可以使得图像匹配精度提高，还能改善局部极值的问题，再利用小波分解对图像进行压缩降低分辨率，可以减少互信息计算量。最后的实验数据表明在配准过程中互信息的计算速度得到了优化，匹配精度得到了提高，实现快速和精确匹配。- Infrared and visible light matching tracking has wide application in military, remote sensing and other fields. There is a relatively large difference for grayscale image features infrared and visible light images, this article uses the maximum mutual information algorithm, combined with morphological gradient and wavelet decomposition. Mutual information algorithm the advantage not need to make any assumptions about the relationship between the multi-mode image gray inadequacies that its image spatial information is ignored and the computation time is longer. This paper mutual information combined with the multi-structural element morphological gradient image edge detection, can make the image matching accuracy is improved, but also to improve the problem of local minima, and then take advantage of the wavelet decomposition to reduce the resolution of the image is compressed, can reduce the amount of mutual information calculated . Finally, the experimental data show that the mutual Platform: |
Size: 280576 |
Author:simon lee |
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Search - edge features tracking