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Publikováno v:
ICARCV
In this paper, we propose an improved fuzzy enhancement algorithm for the moving object detection and tracking. A new membership function is proposed based on the theory of fuzzy sets, which improves the traditional Pal-King fuzzy enhancement algorit
Publikováno v:
2016 International Conference on Information Science (ICIS).
This paper introduces an automatic classification of mammogram images by categorizing malignant or normal after segmenting the suspected region. Fuzzy and fuzzy soft set approaches have been used successfully to deal with diverse uncertainties, impre
Publikováno v:
2016 International Conference on Microelectronics, Computing and Communications (MicroCom).
The paper presents a comparison between different membership functions based type-1 fuzzy set for automatic hand gesture recognition for American Sign Language recognition. First pre-processing of the images is done using skin color based segmentatio
Autor:
Akira Asano, Agus Zainal Arifin, Gulpi Qorik Oktagalu Pratamasunu, Dini Adni Navastara, Zhencheng Hu, Wijayanti Nurul Khotimah, Arya Yudhi Wijaya, Anny Yuniarti
Publikováno v:
IWCIA
In this paper, we propose an automatic image thresholding method based on an index of fuzziness and a fuzzy similarity measure. This work aims at overcoming the limitation of the existing method which is semi-supervised. Using an index of fuzziness,
Autor:
Assas Ouarda
Publikováno v:
International Conference on Computer Vision and Image Analysis Applications.
The imprecision in an image can be expressed in terms of ambiguity of belonging of a pixel in the image or the bottom (if it is black or white), or at the in-definition of the form and the geometry of a region in the image, or the combination of the
Autor:
G. Gendy, R. R. Gharieb
Publikováno v:
2014 Cairo International Biomedical Engineering Conference (CIBEC).
This paper presents a new technique for incorporating local membership information into the standard fuzzy C-means (FCM) clustering algorithm. In this technique, the objective consists of minimizing the classical FCM function with a unity fuzzifier e
Publikováno v:
2013 6th International Congress on Image and Signal Processing (CISP).
The quality of lymph node images is very important for the doctor to do the pathological analysis. For the fuzziness and uncertainty of the edge, the shape and size of lymph nodes, we propose Fuzzy c-Means (FCM) peak clustering which sharpens blurry
Publikováno v:
SoCPaR
In this paper, an image thresholding method based on Intuitionistic Type-2 Fuzzy Sets (InT2FS) method is introduced for the segmentation problems. Besides, intuitionistic type-2 fuzzy set has been formed as an extension of intuitionistic fuzzy set fo
Publikováno v:
2013 International Conference on Open Source Systems and Technologies.
In this paper, we proposed a new approach for image clustering to address the adverse effects of noise presented in the images. In particular, the concept of information gain has been incorporated into classical fuzzy c-means (FCM) algorithm in order
Autor:
Leyuan Fang, Juan Yang
Publikováno v:
2013 Chinese Automation Congress.
This paper presents a novel method for extracting road from high resolution remote sensing image based on Gaussian mixture model and Markov random field (GMM-MRF) model optimized by the iterated conditional model (ICM). In this paper, we first divide