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Edge detection is an essential method used in the image processing systems and can be applied to image sets before the training phase in pattern recognition systems. An edge detector simplifies the analysis of the images; because, it reduces the dataset processed. In this paper we present the advantage to use a fuzzy edge detector method in a face recognition system. In the methodology, first the...
In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals for combining multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition. In this paper, the focus is on aggregation operators that use measures...
In this paper a new method for response integration, based on the Choquet Integral with Interval type-2 Sugeno measures is presented. The Choquet integral is used as a method to integrate the outputs of the modules of the modular neural networks (MNN). The fuzzy Sugeno measures of the Choquet integral are represented by an interval type-2 fuzzy system. A database of faces was used to perform the preprocessing,...
This paper presents an edge-detection method that is based on the morphological gradient technique and generalized type-2 fuzzy logic. The theory of alpha planes is used to implement generalized type-2 fuzzy logic for edge detection. For the defuzzification process, the heights and approximation methods are used. Simulation results with a type-1 fuzzy inference system, an interval type-2 fuzzy inference...
Edge detection in an image is one of the most important tasks when working with image recognition, object identification, feature extraction, among others. There are different metrics to evaluate edges, such as Pratt, Jaccard, Dice but all these metrics binarize the image, and by performing this action information is lost from the image. This paper presents a new method that will allow the evaluation...
This paper presents an edge detection method based on morphological gradient technique and generalized type-2 fuzzy logic. The theory of alpha planes is used to implement generalized type-2 fuzzy logic. For the test we used the method of defuzzification by height and approximation. The simulation results were obtained with a type-1 fuzzy inference system (T1FIS), an interval type-2 fuzzy inference...
This paper presents an edge detection method based on morphological gradient technique and generalized type-2 fuzzy logic. The theory of alpha planes is used to implement generalized type-2 fuzzy logic. The proposed type-2 fuzzy edge detection method was tested with benchmark images to illustrate the advantages of the use of generalized type-2 fuzzy logic.
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