The Otsu's method has been proven as an efficient method in image segmentation for bi-
level thresholding. However, this method is computationally intensive when extended to …

Otsu's method of image segmentation selects an optimum threshold by maximizing the
between-class variance in a gray image. However, this method becomes very time …

This paper presented a hybrid optimal estimation algorithm for solving multi-level
thresholding problems in image segmentation. The distribution of image intensity is modeled …

This chapter proposes a new method for determining the multilevel thresholding values for
image segmentation. The proposed method considers the multilevel threshold as multi …

Segmentation is a crucial step in image processing applications. This process separates
pixels of the image into multiple classes that permits the analysis of the objects contained in …

Variance-based thresholding method is a very effective technology for image segmentation.
However, its performance is limited in traditional one-dimensional and two-dimensional …

There are many techniques for conducting image analysis and pattern recognition. This
papers explores a way to optimize one of these techniques—image segmentation—with the …

Image processing is one of the major research regions in the most recent decades, in which,
image segmentation has gained more popularity due to its enormous applications. Before …

Multi-level thresholding is a helpful tool for several image segmentation applications.
Evaluating the optimal thresholds can be applied using a widely adopted extensive scheme …

Image segmentation is one of the most important tasks in image processing and pattern
recognition. One of the most efficient and popular techniques for image segmentation is …