Search results for "Pattern recognition"
showing 10 items of 2301 documents
A Formalism Supplementing Cognitive Semantics Based on Mereology
2007
ABSTRACT This paper is motivated by and aims to supplement Cognitive Semantics. Details of this latter prominent approach within contemporary linguistic research will not be discussed here. Rather, we focus on a formalization of the concept of Gestalt and provide a formal semantics that can be used to interpret a certain formal language (LM 0) with respect to a universe of structured wholes (Gestalts). Since a great deal of the analyses of linguistic organization that has been provided by Cognitive Semantics since the mid-1970s is based on the concept of Gestalt, the semantics unfolded in the following may be viewed as an attempt to provide a starting point for supplementing the yet informa…
Pattern Recognition: The "Postcinema" Seen by William Gibson
2015
Attraverso la lettura di "Pattern Recognition" di William Gibson possiamo rintracciare i caratteri del Postcinema
Mathematical Morphology for Color Images: An Image-Dependent Approach
2012
This paper proposes one possibility to generalize the morphological operations (particularly, dilation, erosion, opening, and closing) to color images. First, properties of a desirable generalization are stated and a brief review is done on former approaches. Then, the method is explained, which is based on a total ordering of the colors in an image induced by its color histogram; this is valid for just one image and may present problems in smoothly coloured images. To solve these drawbacks a refinement consisting of smoothing the histogram and using a joint histogram of several images is presented. Results of applying the so-defined morphological operations on several sets of images are sh…
Multichannel single-output color pattern recognition by use of a joint-transform correlator.
1996
A novel method for performing color image recognition by the use of the coherent joint-transform correlator is introduced. The input plane of the proposed method is a spatial rearrangement of the separation into color channels of both the color input scene and the color target. This input plane is gray scaled and monochromatic, thus it can be displayed by the use of amplitude spatial light modulators to achieve real-time operation. The system provides a single output-plane result of the optical coherent addition of the separate channels’ correlation outputs. At the output plane no electronic postprocessing is needed, and the detection decision is achieved simply by the application of thresh…
Multi-channel chromatic transformations for nonlinear color pattern recognition
2002
We present a new approach for color pattern recognition based on multi-channel nonlinear correlations. High discrimination capability is obtained in comparison with common linear multi-channel detection methods. We apply the nonlinear morphological correlation to different color channel decompositions as RGB and ATD channels. Moreover, in order to improve the discrimination we have introduced a new color transformation. When a high selectivity is required, the combination of the nonlinear correlation and the new color decomposition yields to detect the object using just a single channel. Simulation results are provided.
A Gamut Preserving Color Image Quantization
2007
International audience; We propose a new approach for color image quantization which preserves the shape of the color gamut of the studied image. Quantization consists to find a set of color representative of the color distribution of the image. We are looking here for an optimal LUT (look up table) which contains information on the image's gamut and on the color distribution of this image. The main motivation of this work is to control the reproduction of color images on different output devices in order to have the same color feeling, coupling intrinsic informations on the image gamut and output device calibration. We have developped a color quantization algorithm based on an image depend…
A Combinatorial Color Edge Detector
2004
In this paper, we present an edge detection approach in color image using neighborhood hypergraph. The edge structure is detected by a structural model. The Color Image Neighborhood Hypergraph (CINH) representation is first computed, then the hyperedges of CINH are classified into noise or edge based on hypergraph properties. To evaluate the algorithm performance, experiments were carried out on synthetic and real color images corrupted by alpha-stable noise. The results show that the proposed edge detector finds the edges properly from color images.
Color and Flow Based Superpixels for 3D Geometry Respecting Meshing
2014
We present an adaptive weight based superpixel segmentation method for the goal of creating mesh representation that respects the 3D scene structure. We propose a new fusion framework which employs both dense optical flow and color images to compute the probability of boundaries. The main contribution of this work is that we introduce a new color and optical flow pixel-wise weighting model that takes into account the non-linear error distribution of the depth estimation from optical flow. Experiments show that our method is better than the other state-of-art methods in terms of smaller error in the final produced mesh.
Perceptual similarity between color images using fuzzy metrics
2016
A method to measure the similarity between color images is proposed.Correlation among the color image channels is taken into account.Proposed similarity measure is based on fuzzy metrics because of their advantages.The proposal matches well with the perceptual visual similarity between color images. In many applications of the computer vision field measuring the similarity between (color) images is of paramount importance. However, the commonly used pixelwise similarity measures such as Mean Absolute Error, Peak Signal to Noise Ratio, Mean Squared Error or Normalized Color Difference do not match well with perceptual similarity. Recently, it has been proposed a method for gray-scale image s…
A neural network based automatic road signs recognizer
2003
Automatic road sign recognition systems are aimed at detection and recognition of one or more road signs from real-world color images. In this research, road signs are detected and extracted from real world scenes on the basis of their color and shape features. A dynamic region growing technique is adopted to enhance color segmentation results obtained in the HSV color space. The technique is based on a dynamic threshold that reduces the effect of hue instability in real scenes due to external brightness variation. Classification is then performed on extracted candidate regions using multilayer perceptron neural networks. The obtained results show good detection and recognition rates of the…