Image segmentation is one of the most important and fundamental tasks in image processing and techniques based on image thresholding are typically simple and computationally efficient. However, the image segmentation results depend heavily on the chosen image thresholding methods. In this paper, histogram is integrated with the Parzen window technique to estimate the spatial probability distrib...

Medical images are corrupted by noises during its transmission and acquisition process. Noise reduction has been a traditional problem in image and signal processing. Medical images generally contains minute information about heart, brain, nerves etc therefore wrong diagnosis might not rescue the patient from harmful effects. In this paper we proposed an approach for image denoising based on wa...

Image thresholding is an important field in image processing. It has been employed to segment the images and extract objects. A variety of algorithms have been proposed in this field. However, these methods perform well on the images without noise, and their results on the noisy images are not good. Neutrosophic set (NS) is a new general formal framework to study the neutralities' origin, natur...

Image acquisition techniques introduce various types of artifacts and noise such as additive white gaussian noise, salt and pepper noise etc, so image denoising is an essential preprocessing step in digital image processing. It is clear from the background study of denoising, conventional methods are not much effective in reducing the noise in the image. In this work, a novel approach which int...

In this work a novel approach for color image segmentation using higher order entropy as a textural feature for determination of thresholds over a two dimensional image histogram is discussed. A similar approach is applied to achieve multi-level thresholding in both grayscale and color images. The paper discusses two methods of color image segmentation using RGB space as the standard processing...

The study presented in this article focuses on comparative analysis of Segmentation techniques. Segmentation techniques are applied to extract Region of Interest (ROI) from medical images obtained from different medical scanners such as Ultrasound, CT or MRI. Global thresholding, Adaptive Thresholding, Region grow and Active contour using level set techniques has been used in the proposed segme...

One of the most straightforward, direct and efficient approaches to Image Segmentation is Image Thresholding. Multi-level Image Thresholding is an essential viewpoint in many image processing and Pattern Recognition based real-time applications which can effectively and efficiently classify the pixels into various groups denoting multiple regions in an Image. Thresholding based Image Segmentati...