Search results for "Pattern"
showing 10 items of 4203 documents
Was heißt wie? Ansatz und Glossar zu Befundung und Verständnis in der HRCT der Lunge
1996
In HRCT reports multiple different, often synonymous, German and English terms are used. The variety of terms impede understanding and acceptance of HRCT. Purpose of this paper is to present a scheme, which is based on the anatomic landmarks (secondary lobule), and the density of pathologic changes, as well as a glossary from the German HRCT-literature, including suitable terms, definitions, synonyms and English terms. Low attenuation changes include emphysemas, air-filled cavities (bullae, cysts, cavitations, honeycombing) and bronchial dilatation, changes with increased density consist of diffuse (ground glass opacity, consolidation) and focal processes (reticular and nodular densities). …
GHOST: GRADIENT HISTOGRAM OF SPECTRAL TEXTURE
2021
International audience; A gradient-based texture feature for hyperspectral image is formulated with straightforward application to grayscale and color images. Processed in full band, GHOST is expressed as a four-dimensional probability density distribution encompassing joint metrological assessment of spectral and spatial properties. Its performance is close to Opponent Band Local Binary Pattern (OBLBP) in HyTexiLa texture classification (91 %-99 % accuracy) with feature size 0.2 % of OBLBP's.
Applying logistic regression to relevance feedback in image retrieval systems
2007
This paper deals with the problem of image retrieval from large image databases. A particularly interesting problem is the retrieval of all images which are similar to one in the user's mind, taking into account his/her feedback which is expressed as positive or negative preferences for the images that the system progressively shows during the search. Here we present a novel algorithm for the incorporation of user preferences in an image retrieval system based exclusively on the visual content of the image, which is stored as a vector of low-level features. The algorithm considers the probability of an image belonging to the set of those sought by the user, and models the logit of this prob…
Spatio-Temporal Saliency Detection in Dynamic Scenes using Local Binary Patterns
2014
International audience; Visual saliency detection is an important step in many computer vision applications, since it reduces further processing steps to regions of interest. Saliency detection in still images is a well-studied topic. However, videos scenes contain more information than static images, and this additional temporal information is an important aspect of human perception. Therefore, it is necessary to include motion information in order to obtain spatio-temporal saliency map for a dynamic scene. In this paper, we introduce a new spatio-temporal saliency detection method for dynamic scenes based on dynamic textures computed with local binary patterns. In particular, we extract l…
Modified morphological correlation based on bit-map representations.
1999
Pattern recognition with high discrimination can be achieved with a morphological correlator. A modification of this correlator is carried out by use of a binary slicing process instead of linear thresholding. Although the obtained correlation result is not identical to the conventional morphological correlation, it requires fewer calculations and provides even higher discrimination. Two optical experimental implementations of this modified morphological correlator as well as some experimental results are shown.
Real And Positive Filter Based On Circular Harmonic Expansion
1989
A real and positive filter for pattern recognition is presented. The filter, based on the circular harmonic (CH) expansion of a real function, is partially rotation invariant. As it is real and positive, the filter can be recorded on a transparency as an amplitude filter. Computer simulations of character recognition show a partial rotation invariance of about 40°. Optical experiments agree with these results and with acceptable discrimination between different characters. Nevertheless, due to experimental difficulties, the method is onerous for use in general pattern recognition problems.
Development of a multispectral imagery device devoted to weed detection
2003
Multispectral imagery is a large domain with number of practical applications: thermography, quality control in industry, food science and agronomy, etc. The main interest is to obtain spectral information of the objects for which reflectance signal can be associated with physical, chemical and/or biological properties. Agronomic applications of multispectral imagery generally involve the acquisition of several images in the wavelengths of visible and near infrared. This paper will first present different kind of multispectral devices used for agronomic issues and will secondly introduce an original multispectral design based on a single CCD. Third, early results obtained for weed detection…
View Planning Approach for Automatic 3D Digitization of Unknown Objects
2012
International audience; This paper addresses the view planning problem for the digitization of 3D objects without prior knowledge on their shape and presents a novel surface approach for the Next Best View (NBV) computation. The proposed method uses the concept of Mass Vector Chains (MVC) to define the global orientation of the scanned part. All of the viewpoints satisfying an orientation constraint are clustered using the Mean Shift technique to construct a first set of candidates for the NBV. Then, a weight is assigned to each mode according to the elementary orientations of its different descriptors. The NBV is chosen among the modes with the highest weights and which comply with the rob…
Towards interpretable classifiers with blind signal separation
2012
Blind signal separation (BSS) is a powerful tool to open-up complex signals into component sources that are often interpretable. However, BSS methods are generally unsupervised, therefore the assignment of class membership from the elements of the mixing matrix may be sub-optimal. This paper proposes a three-stage approach using Fisher information metric to define a natural metric for the data, from which a Euclidean approximation can then be used to drive BSS. Results with synthetic data models of real-world high-dimensional data show that the classification accuracy of the method is good for challenging problems, while retaining interpretability.
PD recognition by means of statistical and fractal parameters and a neural network
2000
A novel partial discharge (PD) defect identification method is described. Starting with PD data on different families of specimens, a suitable set of parameters are determined and then used as input variables to a neural network for the purpose of identifying the defects within the insulation. In this procedure the statistical Weibull analysis is performed on PD pulse amplitude histograms to obtain the scale parameter /spl alpha/ and the shape parameter /spl beta/. Thereafter, the two statistical operators (skewness and kurtosis) and two fractal parameters (fractal dimension and lacunarity) are evaluated from the PD phase on the discharge epoch histogram and from the 3 dimensional (pulse am…