Search results for "Image texture"
showing 10 items of 40 documents
Textile and tile pattern design automatic cataloguing using detection of the plane symmetry group
2004
We present an integrated management system of pattern design for the textile and tile industries providing automatic cataloguing capabilities based on the application of the scientific theory of symmetry groups. To do this, a process of analysis is performed which starts from an initial image of the decorative element, which in turn is subjected to a number of segmentation and labelling operators that allow to detect the objects present in the image. These objects are vectorized, compared, and their isometries obtained; subsequently they are grouped and the isometries of the groups of objects detected. Finally, a composition analysis is carried out that, on the basis of the repetitions and …
<title>Combining multiple image descriptions for browsing and retrieval</title>
2000
Retrieving images form large collections using image content is an important problem, in this multimedia age. A quick content-based visual access to the stored image is capital for efficient navigation through image collections. In this paper we introduce several techniques which characterize color homogeneous object and their spatial relationships for efficient content-based image retrieval. We present a region growing technique for efficient color homogeneous objects segmentation and extend the 2D string to an accurate description of spatial information and relationships. In order to improve content-based image retrieval, our method emphasized several objectives, such as: automated extrac…
A New Wavelet-Based Texture Descriptor for Image Retrieval
2007
This paper presents a novel texture descriptor based on the wavelet transform. First, we will consider vertical and horizontal coefficients at the same position as the components of a bivariate random vector. The magnitud and angle of these vectors are computed and its histograms are analyzed. This empirical magnitud histogram is modelled by using a gamma distribution (pdf). As a result, the feature extraction step consists of estimating the gamma parameters using the maxima likelihood estimator and computing the circular histograms of angles. The similarity measurement step is done by means of the well-known Kullback-Leibler divergence. Finally, retrieval experiments are done using the Bro…
Detecting multiple copies in tampered images
2010
Copy-move forgeries are parts of the image that are duplicated elsewhere into the same image, often after being modified by geometrical transformations. In this paper we present a method to detect these image alterations, using a SIFT-based approach. First we describe a state of the art SIFT-point matching method, which inspired our algorithm, then we compare it with our SIFT-based approach, which consists of three parts: keypoint clustering, cluster matching, and texture analysis. The goal is to find copies of the same object, i.e. clusters of points, rather than points that match. Cluster matching proves to give better results than single point matching, since it returns a complete and co…
Texture analysis and optical anisotropy measurements of leukocytes for early diagnostics of diabetes mellitus
2004
DNA damage had been suggested to contribute to the pathogenesis of insulin dependent diabetes mellitus (IDDM). In this work we present a method for detection and discrimination of such DNA changes by means of analysis of light microscope images of anisotropically stained leukocytes nuclei. Several features of the images have been evaluated, including integrated optical density, degree of polarisation, and textural features. A genetic algorithm, coupled with a neural classifier, has been used to find the best features for identification of the pathology. Reported results indicate the best set is able to achieve an 83% correct classification ratio.
Automated Detection of Optic Disc Location in Retinal Images
2008
This contribution presents an automated method to locate the optic disc in color fundus images. The method uses texture descriptors and a regression based method in order to determine the best circle that fits the optic disc. The best circle is chosen from a set of circles determined with an innovative method, not using the Hough transform as past approaches. An evaluation of the proposed method has been done using a database of 40 images. On this data set, our method achieved 95% success rate for the localization of the optic disc and 70% success rate for the identification of the optic disc contour (as a circle).
An FPGA-based design for real-time Super Resolution Reconstruction
2018
Since several decades, the camera spatial resolution is gradually increasing with the CMOS technology evolution. The image sensors provide more and more pixels, generating new constraints for the suitable optics. As an alternative, promising solutions propose Super Resolution (SR) image reconstruction to extend the image size without modifying the sensor architecture. Convincing state-of art studies demonstrate that these methods could even be implemented in real-time. Nevertheless, artifacts can be observed in highly textured areas of the image. In this paper, we propose a Local Adaptive Spatial Super Resolution (LASSR) method to fix this limitation. A real-time texture analysis is include…
A Clustering Approach to texture Classification
1988
In the paper a clustering technique to segment an image in to “homogeneous” regions is studied. The homogeneity of each region is evaluated by means of a “proximity function” computed between the pixels. The main result of such approach is that no-histogramming is required in order to perform segmentation. Possibilistic and probabilistic approaches are, also, combined to evaluate the significativity of the computed regions.
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…
Automatic texture mapping on real 3D model
2007
We propose a full automatic technique to project virtual texture on a real textureless 3D object. Our system is composed of cameras and projector and are used to determine the pose of the object in the real world with the projector as reference and then estimate the image seen by the projector if it would be a camera.