Search results for "Pattern recognition"
showing 10 items of 2301 documents
Adapted processing of catadioptric images using polarization imaging
2009
A non parametric method that defines a pixel neighborhood within catadioptric images is presented in this paper. It is based on an accurate modeling of the mirror shape by using polarization imaging. Unlike the most of current processing methods in the literature, this method is non-parametric and can deal with the deformation of catadioptric images. This paper demonstrates how an appropriate neighborhood can be derived from the polarization parameters by estimation of the degree of polarization and the angle of polarization which in return directly provide an adapted neighborhood of each pixel that can be used to perform image derivation, edge detection, interest point detection and namely…
<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…
Texture Discrimination Using Hierarchical Complex Networks
2008
Texture analysis represents one of the main areas in image processing and computer vision. The current article describes how complex networks have been used in order to represent and characterized textures. More speci?cally, networks are derived from the texture images by expressing pixels as network nodes and similarities between pixels as network edges. Then, measurements such as the node degree, strengths and clustering coe?cient are used in order to quantify properties of the connectivity and topology of the analyzed networks. Because such properties are directly related to the structure of the respective texture images, they can be used as features for characterizing and classifying te…
Meta-Tracking for Video Scene Understanding
2013
International audience; This paper presents a novel method to extract dominant motion patterns (MPs) and the main entry/exit areas from a surveillance video. The method first computes motion histograms for each pixel and then converts it into orientation distribution functions (ODFs). Given these ODFs, a novel particle meta-tracking procedure is launched which produces meta-tracks, i.e. particle trajectories. As opposed to conventional tracking which focuses on individual moving objects, meta-tracking uses particles to follow the dominant flow of the traffic. In a last step, a novel method is used to simultaneously identify the main entry/exit areas and recover the predominant MPs. The meta…
Affine camera calibration from homographies of parallel planes
2010
This paper deals with the problem of retrieving the affine structure of a scene from two or more images of parallel planes. We propose a new approach that is solely based on plane homographies, calculated from point correspondences, and that does not require the recovery of the 3D structure of the scene. Neither vanishing points nor lines need to be extracted from the images. The case of a moving camera with constant intrinsic parameters and the one of cameras with possibly different parameters are both addressed. Extensive experiments with both synthetic and real images have validated our approach.
Image Compression by 2D Motif Basis
2011
Approaches to image compression and indexing based on extensions to 2D of some of the Lempel-Ziv incremental parsing techniques have been proposed in the recent past. In these approaches, an image is decomposed into a number of patches, consisting each of a square or rectangular solid block. This paper proposes image compression techniques based on patches that are not necessarily solid blocks, but are affected instead by a controlled number of undetermined or don't care pixels. Such patches are chosen from a set of candidate motifs that are extracted in turn from the image 2D motif basis, the latter consisting of a compact set of patterns that result from the autocorrelation of the image w…
Smartphone determination of fat in cured meat products
2017
Abstract A method has been developed to determine the fat content in different cold meat products by image processing using the camera of a mobile phone. Salchichon , chorizo , salami and cured ham pictures were taken with a Meizu M2 Mini mobile phone camera under fixed lighting conditions of the light emitting diode flash of the mobile phone. Images were treated with Matlab to obtain the mean pixels of average red, green and blue camera values colours (RGB) of the pixels and different data pretreatments were taken into account to correlate colour parameters with fat content values determined in a series of commercially available samples by the Soxhlet method. RGB values were used as input …
Maximum likelihood for target location in the presence of substitutive noise .
2001
We consider the optimal likelihood algorithm for the estimation of a target location when the images are corrupted by substitutive noise. We show the relationship between the optimal algorithm and the sliced orthogonal nonlinear generalized (SONG) correlation. The SONG correlation is based on the application of a linear correlation to corresponding binary slices of both the input scene and the reference object with appropriate weight factors. For a particular case, we show that the optimal strategy is a function of only the number of pixels for which the gray values in the noisy image match the ones of the reference image when the substitutive noise is uniformly distributed. This is exactly…
Architectural Scenes Reconstruction from Uncalibrated Photos and Map Based Model Knowledge
2001
In this paper we consider the problem of reconstructing architectural scenes from multiple photographs taken from arbitrarily viewpoints. The original contribution of this work is the use of a map as a source of a priori knowledge and geometric constraints in order to obtain in a fast and simple way a detailed model of a scene. We suppose images are uncalibrated and have at least one planar structure as a facade for exploiting the planar homography induced between world plane and image to calculate a first estimation of the projection matrix. Estimations are improved by using correspondences between images and map. We show how these simple constraints can be used to calibrate the cameras, t…