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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 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
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
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
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
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:
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
Automatic face recognition is an important and complex task. Therefore, it is necessary to design efficient algorithms able to cope with all the different problems of face recognition. Thus, a great progress has been done using the actual vision tech
Publikováno v:
FUZZ-IEEE
For applications like scene classification, CBIR, automated tagging, motion of a robot in a real world using vision system, understanding the images captured by the visual sensors is quite important. For such high level processing task it is mandator
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