Add to ORKGIn this paper we present a neuro-fuzzy approach for classification of image pixels into three classes: contour, regular or texture points. Exploiting the processing capabilities of a neural network, fuzzy classification rules are derived by learning from data and applied to classify pixels in grey-level images. To derive a proper set of training data, the spatial properties of the image features and a multi-scaled representation of images are considered. The effectiveness of the proposed approach is illustrated on some sample images
In this paper texture classification is studied based on the fractal dimension (FD) of filtered vers...
This paper describes an approach to classification of noisy signals using a technique based on the f...
This paper describes an approach to classification of noisy signals using a technique based on the f...
This work presents a methodology to tackle the problem of classifying the pixels of a given image in...
The employment of image processing techniques appears to be wide-spreading in several application ar...
Classification of texture pattern is one of the most important problems in pattern recognition. In t...
This paper describes an approach to classification of textured grayscale images using a technique ba...
Classification of texture patterns is one of the most important problems in pattern recognition. In ...
This paper describes an approach to classification of textured grayscale images using a technique ba...
[[abstract]]An unsupervised classification technique conceptualized in terms of neural and fuzzy dis...
This paper presents a new technique to extract, in noisy digital pictures, regions whose pixels fall...
The relevance of integration of the merits of fuzzy set theory and neural network models for designi...
Abstract. Our special fuzzy classifier operates on the set of eight features extracted from the 3x3 ...
[[abstract]]An unsuperivsed classification approach conceptualized in terms of neural and fuzzy disc...
This paper is concerned with the application of an enhanced Fuzzy ART neural network algorithm for c...
In this paper texture classification is studied based on the fractal dimension (FD) of filtered vers...
This paper describes an approach to classification of noisy signals using a technique based on the f...
This paper describes an approach to classification of noisy signals using a technique based on the f...
This work presents a methodology to tackle the problem of classifying the pixels of a given image in...
The employment of image processing techniques appears to be wide-spreading in several application ar...
Classification of texture pattern is one of the most important problems in pattern recognition. In t...
This paper describes an approach to classification of textured grayscale images using a technique ba...
Classification of texture patterns is one of the most important problems in pattern recognition. In ...
This paper describes an approach to classification of textured grayscale images using a technique ba...
[[abstract]]An unsupervised classification technique conceptualized in terms of neural and fuzzy dis...
This paper presents a new technique to extract, in noisy digital pictures, regions whose pixels fall...
The relevance of integration of the merits of fuzzy set theory and neural network models for designi...
Abstract. Our special fuzzy classifier operates on the set of eight features extracted from the 3x3 ...
[[abstract]]An unsuperivsed classification approach conceptualized in terms of neural and fuzzy disc...
This paper is concerned with the application of an enhanced Fuzzy ART neural network algorithm for c...
In this paper texture classification is studied based on the fractal dimension (FD) of filtered vers...
This paper describes an approach to classification of noisy signals using a technique based on the f...
This paper describes an approach to classification of noisy signals using a technique based on the f...