In this paper, first some characterization of various fuzzy bounded sets in FM-spaces are given. Some important fixed point theorems for multi-valued mappings in FM-spaces will be given.

Some Results on Fuzzy Metric Spaces

In this paper, the problem of impulsive noise reduction in multichannel images is addressed. A new filter is proposed on the basis of a recently introduced family of computationally attractive filters with a good detail-preserving ability (FSVF). FSVF is based on privileging the central pixel in each filtering window in order to replace it only when it is really noisy and preserve the original undistorted image structures. The new filter is based on a novel fuzzy metric and it is created by combining the mentioned scheme and the fuzzy metric. The use of the fuzzy metric makes the filter computationally simpler and it allows to adjust the privilege of the central pixel giving the filter an adaptive nature. Moreover, it is shown that the new filter outperforms the classical-order statistics filtering techniques and its performance is similar to FSVF, outperforming it in some cases.

A fast impulsive noise color image filter using fuzzy metrics

The peer group of an image pixel is a pixel similarity-based concept which has been successfully used to devise image denoising methods. However, since it is difficult to define the pixel similarity in a crisp way, we propose to represent this similarity in fuzzy terms. In this paper, we introduce the fuzzy peer group concept, which extends the peer group concept in the fuzzy setting. A fuzzy peer group will be defined as a fuzzy set that takes a peer group as support set and where the membership degree of each peer group member will be given by its fuzzy similarity with respect to the pixel under processing. The fuzzy peer group of each image pixel will be determined by means of a novel fuzzy logic-based procedure. We use the fuzzy peer group concept to design a two-step color image filter cascading a fuzzy rule-based switching impulse noise filter by a fuzzy average filtering over the fuzzy peer group. Both steps use the same fuzzy peer group, which leads to computational savings. The proposed filter is able to efficiently suppress both Gaussian noise and impulse noise, as well as mixed Gaussian-impulse noise. Experimental results are provided to show that the proposed filter achieves a promising performance.

Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images

A new adaptive center weighted median filter for suppressing impulsive noise in images

Examples of fuzzy metrics and applications

Vector median filtering is a well known technique for reducing noise in color images These filters are defined on the basis of a suitable distance or similarity measure, being the most common used the Euclidean and City-Block distances In this paper, a Fuzzy Metric, in the sense of George and Veeramani (1994), is defined and applied to color image filtering by means of a new Vector Median Filter It is shown that the standard Vector Median Filter is outperformed when using this Fuzzy Metric instead of the Euclidean and City-Block distances

A new vector median filter based on fuzzy metrics

Probably, the most well-known vector filter is the vector median filter (VMF) which is based on the theory of robust statistics and performs good noise suppression in color images. However, the VMF is designed to perform a fixed amount of smoothing. This may lead to too much unnecessary substitutions in the input image and, as a result, blurring and loss of image details. In order to avoid this drawback when dealing with impulsive noise, the switching schemes aim at selecting a set of pixels of the input image to be filtered leaving the rest of the pixels unchanged. In this paper, two switching filters which base the selection of the noisy pixels to be filtered on statistical tests are proposed. The proposed filters present good noise suppression while preserving fine image details appropriately. Comparisons to classical and recently introduced impulsive noise multichannel filters are provided. Moreover, the noisy pixel selection techniques are computationally simple, and the filters significantly reduce the computational complexity of the VMF.

Efficient impulsive noise suppression based on statistical confidence limits

Hoy en dia la industria del pavimento y revestimiento ceramico espanol produce mas de 600 MMm2 al ano, debiendo, cada
pieza ser inspeccionada y clasificada en la mayoria de las empresas. Ello implica que normalmente cada modelo debe de ser
almacenado por subgrupos en funcion del tono y del calibre, lo que supone la necesidad de un sistema de almacenamiento
y distribucion que tenga en consideracion estos elementos.
El impacto economico derivado precisamente de la necesidad de un control de stocks, se ve incrementado en lo que se refiere
al control del aspecto visual (relacionado con el diseno y el color). Esta clasificacion es susceptible de ser automatizada,
pero este procedimiento parece no haberse impuesto claramente frente a procesos de clasificacion visuales realizados por
clasificadores profesionales. La gran complejidad de los modelos, la dificultad en la definicion de los criterios de clasificacion,
y la falta de criterios objetivos y repetibles para todos los disenos son cuestiones que dificultan la automatizacion de este
proceso crucial de la cadena de produccion.
Precisamente para estudiar el control cromatico de las baldosas, es necesario hacer un analisis a fondo del proceso de
clasificacion ceramico. En este trabajo se estudia la clasificacion tonal, resaltando las caracteristicas tecnologicas y de
investigacion mas resenables en los ultimos cincuenta anos, asi como sus perspectivas de futuro.

/pdf/analisis-del-proceso-de-clasificacion-ceramico-35wze9lc5l.pdf

Análisis del proceso de clasificaciÓn ceràmico

The manufacturing of ceramic tiles is a very complex process, where a wide range of variables has an important influence in the final product. With regard to external appearance, the most of the production defects take place in the decoration station. Nevertheless, these defects are usually detected before baking, when the product is already finished, causing an important loss of effectives. Under this perspective, a mechanism able to detect the printing defects in the green parts would achieve 2 goals: on one hand, the reduction of the nonquality costs since green parts can be more easily recycled; and on the other hand, it would point out the real root cause of the failure by indicating, for instance, which ink is causing the problem. Color Prediction Models (CPM) are mathematical approaches which relate the microscopic distribution of the printed dots of a halftone image with the resulting macroscopic color. Its usage is extended in the field of the Graphic Arts, especially for calibration and fine image reproduction. However, they are barely known in the ceramic tile industry, a sector that keeps many similarities with the Graphic Arts one in terms of decorating. In this paper, we analyzed the prediction quality of 4 successful CPM (Murray- Davies, Yule-Nielsen, Neugebauer and Neugebauer Modified Yule-Nielsen) on 1 and 2 inks halftones printed on ceramic sub- strates, setting a comparison between them by means of linear and non-linear optimization techniques. Moreover, we proposed av alue for the enigmatic"n"parameter on ceramic surfaces, which is said to model the optical dot gain phenomenon.

/pdf/evaluation-of-color-prediction-models-in-the-decoration-of-2q7nmllh3w.pdf

Pedro Latorre

Papers

A fast impulsive noise color image filter using fuzzy metrics

A new vector median filter based on fuzzy metrics

Efficient impulsive noise suppression based on statistical confidence limits

Análisis del proceso de clasificaciÓn ceràmico

Evaluation of color prediction models in the decoration of ceramic tiles