Abstract. This paper presents a novel histogram thresholding technique based on the beam theory of solid mechanics and the minimization of ambiguity in information. First, a beam theory based histogram modification process is carried out. This beam theory based process considers a distance measure in order to modify the shape of the histogram. The ambiguity in the overall information given by the modified histogram is then minimized to obtain the threshold value. The ambiguity minimization is carried out using the theories of fuzzy and rough sets, where a new definition of rough entropy is presented. The applications of the proposed scheme in performing object and edge extraction in images are reported and compared with those of a few exist...
Abstract—Methods for histogram thresholding based on the minimization of a threshold-dependent crite...
Selecting a threshold from the gradient histogram, a histogram of gradient magnitudes, of an image p...
Though traditional thresholding methods are simple and efficient, they may result in poor segmentati...
This paper presents a novel histogram thresholding technique based on the beam theory of solid mecha...
This paper presents a novel histogram thresholding methodology using fuzzy and rough set theories. T...
Image segmentation plays an important role in various image processing applications including robot ...
Histogram Thresholding is an image processing technique whose aim is that of separating the objects ...
The problem of Histogram sharpening and thresholding by minimizing greyness ambiguity using the meas...
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. ...
This paper describes an automatic threshold selection method for picture segmentation, using the ent...
The entropy method for image thresholding suggested by Kapur et al. has been modified and a more per...
This paper describes an automatic threshold selection method for picture segmentation. The basic con...
[[abstract]]This paper introduces a new image thresholding method based on minimizing the measures o...
The problem of histogram sharpening and thresholding by minimising greylevel fuzziness is considered...
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. ...
Abstract—Methods for histogram thresholding based on the minimization of a threshold-dependent crite...
Selecting a threshold from the gradient histogram, a histogram of gradient magnitudes, of an image p...
Though traditional thresholding methods are simple and efficient, they may result in poor segmentati...
This paper presents a novel histogram thresholding technique based on the beam theory of solid mecha...
This paper presents a novel histogram thresholding methodology using fuzzy and rough set theories. T...
Image segmentation plays an important role in various image processing applications including robot ...
Histogram Thresholding is an image processing technique whose aim is that of separating the objects ...
The problem of Histogram sharpening and thresholding by minimizing greyness ambiguity using the meas...
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. ...
This paper describes an automatic threshold selection method for picture segmentation, using the ent...
The entropy method for image thresholding suggested by Kapur et al. has been modified and a more per...
This paper describes an automatic threshold selection method for picture segmentation. The basic con...
[[abstract]]This paper introduces a new image thresholding method based on minimizing the measures o...
The problem of histogram sharpening and thresholding by minimising greylevel fuzziness is considered...
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. ...
Abstract—Methods for histogram thresholding based on the minimization of a threshold-dependent crite...
Selecting a threshold from the gradient histogram, a histogram of gradient magnitudes, of an image p...
Though traditional thresholding methods are simple and efficient, they may result in poor segmentati...