Search results for "GEP"
showing 10 items of 1017 documents
Cluster kernels for semisupervised classification of VHR urban images
2009
In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and wor…
A Statistical Matrix Representation Using Sliced Orthogonal Nonlinear Correlations for Pattern Recognition
2000
In pattern recognition, the choice of features to be detected is a critical factor to determine the success or failure of a method; much research has gone into finding the best features for particular tasks [1]. When images are detected by digital cameras, they are usually acquired as rectangular arrays of pixels, so the initial features are pixel values. Some methods use those pixel values directly for processing, for instance in normal matched filtering [2], whereas other methods execute some degree of pre-processing, such as binarizing the pixel values [3].
Selective Change Driven Vision Sensor With Continuous-Time Logarithmic Photoreceptor and Winner-Take-All Circuit for Pixel Selection
2015
The objective of Selective Change Driven (SCD) Vision is to capture and process those scene pixels that have the greatest impact in the motion estimation task. The implemented SCD Vision sensor delivers the pixels ordered according to the illumination change undergone by each pixel, from the last time each pixel was read-out. This ordering strategy is especially interesting for motion detection algorithms, since it allows for a reduction in data bandwidth requirements without decreasing accuracy. The speed of the obtained pixel flow allows movement detection and tracking at a speed several orders of magnitude higher than conventional vision systems. To accomplish these objectives, the senso…
A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC
2009
This paper presents a comparative study on five feature selection heuristics applied to a retinal image database called DRIVE. Features are chosen from a feature vector (encoding local information, but as well information from structures and shapes available in the image) constructed for each pixel in the field of view (FOV) of the image. After selecting the most discriminatory features, an AdaBoost classifier is applied for training. The results of classifications are used to compare the effectiveness of the five feature selection methods.
Improving SIFT-based descriptors stability to rotations
2010
Image descriptors are widely adopted structures to match image features. SIFT-based descriptors are collections of gradient orientation histograms computed on different feature regions, commonly divided by using a regular Cartesian grid or a log-polar grid. In order to achieve rotation invariance, feature patches have to be generally rotated in the direction of the dominant gradient orientation. In this paper we present a modification of the GLOH descriptor, a SIFT-based descriptor based on a log-polar grid, which avoids to rotate the feature patch before computing the descriptor since predefined discrete orientations can be easily derived by shifting the descriptor vector. The proposed des…
Extract information of polarization imaging from local matching stereo
2010
Since polarization of light was used in the field of computer vision, the research of polarization vision is rapidly growing. Polarization vision has been shown to simplify some important image understanding tasks that can be more difficult to be performed with intensity vision. Furthermore, it has computational efficiency because it only needs grayscale images and can be easily applied by a simple optical setup. Nowadays, we can find various types of polarization cameras in the market. However, they are very expensive. In our work, we will study and develop a low price polarization camera setup with parallel acquisition using a stereo system. This system requires only two general cameras e…
Choosing local matching score method for stereo matching based-on polarization imaging
2010
Polarization imaging is a powerful tool to observe hidden information from an observed object. It has significant advantages, such as computational efficiency (it only needs gray scale images) and can be easily applied by adding a polarizer in front of a camera. Many researchers used polarization in various areas of computer vision, such as object recognition, segmentation and so on. However, there is very little research in stereo vision based on polarization. Stereo vision is a well known technique for obtaining depth information from pairs of stereo digital images. One of the main focuses of research in this area is to get accurate stereo correspondences. In our work, we will study and d…
Estimating intrinsic image from successive images by solving underdetermined and overdetermined systems of the dichromatic model
2020
International audience; Estimating an intrinsic image from a sequence of successive images taken from an object at different angles of illumination can be used in various applications such as objects recognition, color classification, and the like; because, in so doing, it can provide more visual information. Meanwhile, according to the well-known dichromatic model, each image can be considered a linear combination of three components, including intrinsic image, shading factor, and specularity. In this study, at first, two simple independent constrained and parallelized quadratic programming steps were used for computing values of the shading factor and the specularity of each successive of…
<title>Spectral/spatial integration effects on information extraction from multispectral data: multiresolution approaches</title>
1995
New techniques for information extraction from multispectral data require physical modeling to understand the energy transfer at the atmosphere/surface interface and to develop appropriate inversion procedures, in combination with advanced processing techniques. A multi-step procedure is proposed in this work: the first step implies a binary decision about the second step to be applied in each case. If the pixel is considered as being a `pure' pixel, through a spectral/spatial classification procedure based on multiresolution techniques, then numerical inversion techniques, based on a multiple-scattering reflectance model, are used to extract parameters representing specific surface propert…
Image Colorization Method Using Texture Descriptors and ISLIC Segmentation
2017
We present a new colorization method to assign color to a grayscale image based on a reference color image using texture descriptors and Improved Simple Linear Iterative Clustering (ISLIC). Firstly, the pixels of images are classified using Support Vector Machine (SVM) according to texture descriptors, mean luminance, entropy, homogeneity, correlation, and local binary pattern (LBP) features. Then, the grayscale image and the color image are segmented into superpixels, which are obtained by ISLIC to produce more uniform and regularly shaped superpixels than those obtained by SLIC, and the classified images are further post-processed combined with superpixles for removing erroneous classific…