Multi-level thresholding of a gray image is one of the basic operations in computer vision,
with applications in image enhancement and segmentation. Various criteria for the selection …

Image thresholding is a very common image processing operation, since almost all image
processing schemes need some sort of separation of the pixels into different classes. In …

One of the most important methods of image processing is image thresholding, which is
based on image histogram analysis. These methods analyze the image histogram diagram …

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 …

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 …

The modified two-stage multithreshold Otsu (TSMO) method based on a twostage Otsu
optimization approach is proposed for multilevel thresholding. The proposed method yields …

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 …

Multilevel thresholding of images helps in separating the interesting objects from their
background. The quality of separation depends much on the selected threshold values. This …

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 …

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 …