Many efficient bi-level thresholding techniques have been proposed in recent years.
Usually, the objective functions, which are used by them, are not appropriate for the …

Image thresholding is an important technique for image processing and pattern recognition.
Many thresholding techniques have been proposed in the literature. Among them, the …

Multilevel thresholding is to find the thresholds to segment the image with grey levels.
Usually, the thresholds are so determined that some indicator functions of the segmented …

Color image thresholding is a well-known approach for image segmentation. An objective
function, based on image entropy, is defined by threshold numbers and locations in the color …

In this paper, a hybrid approach, which is based on Gaussian smoothing and a genetic
algorithm (GA), is proposed for automatic multilevel image thresholding. Using a mixture …

Multilevel image thresholding is a challenging digital image processing problem with
numerous applications, including image segmentation, image analysis and higher level …

Image segmentation is a technique of subdividing an image into numerous sections that
converts an image into more expressive form that is easier to analyze. Histogram is one of …

Entropy-based image thresholding are used widely in image processing. Conventional
methods are efficient in the case of bilevel thresholding. But they are very computationally …

In this paper, we present a new multi-level image thresholding technique, called Automatic
Threshold based on Multi-objective Optimization “ATMO” that combines the flexibility of multi …

Image thresholding is usually applied as an initial step in many algorithms for image
analysis, object representation and visualization. Although many image thresholding …