Description: 基于链码提取的傅立叶描述子,以及傅立叶反变换对图象边界进行重建
-chain code extraction based on Fourier descriptors, and the Fourier transform of image reconstruction border Platform: |
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Author:ff |
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Description: 在图像处理中 基于形状的描述符 特别是基于轮廓的算法是以识别轮廓为基础的 此代码能够准确，快速地分割图像。-in image processing based on the shape of the descriptor is based on the outline in particular the recognition algorithm is based on the contours of this generation code to be accurate, and fast image segmentation. Platform: |
Size: 56320 |
Author:xiaoqi |
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Description: Lire 0.7 is a major release fixing a lot of bugs and introducing several new features including new descriptor, a simplified way to use descriptors by introducing new generic searchers and indexers as well as an generalized interface for image descriptors. There are also several improvements in indexing and search speed (especially in autocolorcorrelogram). Furthermore retrieval performance was optimized based on the Wang 1000 data set. If you use Lire 0.7 to update an existing version, please make sure that your indices are created newly from scratch. Platform: |
Size: 155648 |
Author:chenglong |
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Description: DCT域中MPEG7主色描述符的提取,该文在MPEG7的基础上提出了DCT域内直接提取主色描述符的新方法.这种方法节省了
对图像的解压缩的过程，因而大大的提高了对于压缩图像进行特征提取的速度和效果.作为整个算法的一部
分，一种自动阂值提取的算法也在该文中给予了描述.这种方法可以减少因人为设定经验闭值而带来的不确
定性，使算法更具鲁棒性.对比检索试验结果也说明本算法是一个高速有效的算法.新算法主要用于压缩图
像库或互联网上的相似检索.
-DCT domain MPEG7 Dominant Color descriptor extraction, the article at the basis of MPEG7 proposed DCT domain directly from the main color of the new method descriptor. This method saves the image in the process of decompression, which greatly enhance the compressed image for feature extraction speed and effectiveness. as part of the whole algorithm, an automatic threshold algorithm for extracting the text is also given to the description. This method can reduce the threshold to set the experience brought about by non- uncertainty, so that a more robust algorithm. Comparison Search results also shows that the algorithm is a fast and effective algorithm. The new algorithm used to compress the image database or a similar search on the Internet. Platform: |
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Author:杨康 |
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Description: 计算图像的描述子算法，使用LabVIEW调用matlab程序实现处理与显示-Image descriptor calculation algorithm, using the LabVIEW program called matlab processing and display Platform: |
Size: 355328 |
Author:高健 |
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Description: 状是含有高层语义信息的视觉特征，在基于内容的图像检索及图像识别中具有重要的应用价值。有很多种描述子可以描述图像的形状特征，傅立叶描述子可以把二维的图像轮廓信息简化成一维问题进行处理，应用非常广泛。然而自然图像的形状特征通常是杂乱的，有噪声的，提出了一种图像预处理方法，得到净化的形状图像，通过实验研究傅立叶描述子算法提取形状特征的效果。-Abstract Shape is a visual feature which contains intrinsic high-level semantics, and has a great application value in CBIR(Content-Based Image Retrieval) and IR(Image Recognition). There are many descriptors for shape feature. Fourier descriptor predigests 2-demensional image information to 1-demensional signal and be used widely. In fact, the shape of natural image is often messy and noisy. So, this paper proposes a preprocessing method which can clean the noisy shape image, and then researches and analyses the shape feature extraction with Fourier descriptor method with an experiment.
Keywords Shape, Fourier Descriptor, Feature Extraction, CBIR(Content-Based Image R
Platform: |
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Author:倪晓雷 |
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Description: extract dense sift for each image patch, because no salient keypoint detection and rotation normalization, it is very efficient. Platform: |
Size: 2048 |
Author:郭恺 |
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Description: In this paper, a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust
Features) is presented. It approximates or even outperforms previously proposed
schemes with respect to repeatability, distinctiveness, and robustness, yet
can be computed and compared much faster.
This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a
distribution-based descriptor) and by simplifying these methods to the
essential. This leads to a combination of novel detection, description, and
matching steps. The paper presents experimental results on a standard
evaluation set, as well as on imagery obtained in the context of a real-life
object recognition application. Both show SURF’s strong performance.-In this paper, a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust
Features) is presented. It approximates or even outperforms previously proposed
schemes with respect to repeatability, distinctiveness, and robustness, yet
can be computed and compared much faster.
This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a
distribution-based descriptor) and by simplifying these methods to the
essential. This leads to a combination of novel detection, description, and
matching steps. The paper presents experimental results on a standard
evaluation set, as well as on imagery obtained in the context of a real-life
object recognition application. Both show SURF’s strong performance. Platform: |
Size: 686080 |
Author:yangwei |
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Description: The matlab source code for the paper "A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration". This paper has been accepted by IEEE Transaction on Biomedical Engineering.-The matlab source code for the paper "A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration". This paper has been accepted by IEEE Transaction on Biomedical Engineering. Platform: |
Size: 20480 |
Author:陈健 |
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Description: 加州大学一博士写的基于sift的图像匹配源代码,是用的matlab和VC混合编程-Ph.D. University of California, to write a sift-based image matching source code, is mixed with the matlab and VC programming Platform: |
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Author:yisyf |
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Description: 一种基于细节点局部描述子的指纹图像匹配方法A local descriptor based on minutiae matching method for fingerprint image-A local descriptor based on minutiae matching method for fingerprint image Platform: |
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Author:boyc121 |
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Description: Image descriptor based on Histogram of Orientated Gradients for gray-level images. This code
was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE
Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437. In
case of publication with this code, please cite the paper above.- Image descriptor based on Histogram of Orientated Gradients for gray-level images. This code
was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE
Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437. In
case of publication with this code, please cite the paper above. Platform: |
Size: 2048 |
Author:Arij |
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Description: description de forme en utilisant FD coeeficeients Fourier utilisé pour la classification forme.
les étapes:
1. trouver les indices de frontières de l image de tranchant (binaire d entrée bordée d image voir le test par exemple)
2. trier les indices de sorte qu ils afin de distance
3. faire des complexes x + jy vecotr
4 Assurez-fft
5 prendre la première FD
6. font IFFT
link (http://www.mathworks.com/matlabcentral/fileexchange/26810-fourier-descriptor)-description de forme en utilisant FD coeeficeients Fourier utilisé pour la classification forme.
les étapes:
1. trouver les indices de frontières de l image de tranchant (binaire d entrée bordée d image voir le test par exemple)
2. trier les indices de sorte qu ils afin de distance
3. faire des complexes x + jy vecotr
4 Assurez-fft
5 prendre la première FD
6. font IFFT
link (http://www.mathworks.com/matlabcentral/fileexchange/26810-fourier-descriptor) Platform: |
Size: 2048 |
Author:chekos |
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Description: Recent innovations in training deep convolutional neural network models have motivated the design of new methods to automatically learn local image descriptors. The latest deep ConvNets proposed for this task consist(from machine learning show that replacing this siamese by a triplet network can improve the classification accuracy in several problems, but this has yet to be demonstrated for local image descriptor learning. Moreover, current siamese and triplet networks have been trained with stochastic gradient descent that computes) Platform: |
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Author:songggg |
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