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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:
SMC
This paper introduces some new image segmentation methods in the framework of shadowed c-means clustering. By implanting the local and non-local spatial information in the membership value estimation procedure, we propose the Local Spatial Shadowed C
Publikováno v:
ICIP
Conventional fuzzy C-means (FCM) algorithm does not consider spatial information in the clustering, which makes it sensitive to noise and inefficient. In order to overcome these problems, we propose a fast anti-noise FCM algorithm for image segmentat
Publikováno v:
ICIP
Extraction of thin elongated objects from natural images is an important task in many computer vision applications such as image segmentation, object detection. Extensive approaches attempt to solve this issue with region features or prior knowledge,
Publikováno v:
ICIP
Fuzzy c-means (FCM) has been considered as an effective algorithm for image segmentation. However, it lacks of sufficient robustness to image noise. In this paper, we propose a simple and effective method to make the traditional FCM more robust to no
Publikováno v:
FUZZ-IEEE
Automatic segmentation of Magnetic Resonance Images (MRI) for tissue classification becomes more challenging when the image is corrupted with noise and intensity non-uniformity (INU). Several fuzzy clustering based statistical retrospective methods e
Publikováno v:
IGARSS
A Quantum-Modeled Fuzzy C-Means clustering algorithm for remotely sensed multi-band image segmentation is explored and evaluated. Data sets of interest include remotely sensed multi-band imagery, which subsequent to classification is analyzed and ass
Publikováno v:
FUZZ-IEEE
In this paper we axiomatically define weak homogeneity of a fuzzy subset, which means that its membership function fulfills at least the minimum properties required to represent the homogeneity of a region. We also provide several construction method
Publikováno v:
CVPR Workshops
We present a new approach to the collection and labeling of ground truth data for annotation of temporal events in ad-hoc videos taken by active operators recording interactions and activities in the field. We present experimental data and related re
Publikováno v:
2013 25th Chinese Control and Decision Conference (CCDC).
Fuzzy C-means clustering (FCM) algorithm is good at solving the ambiguities and uncertainties in the image, and the modified FCM has been widely used in solving the intensity inhomogeneity problem. Bias-corrected FCM (BCFCM) is very useful for noise