Numerous techniques have previously been proposed for single-stage thresholding of document images to separate the written or printed information from the background. Although these global or local thresholding techniques have proven effective on particular subclasses of documents, none is able to produce consistently good results on the wide range of document image qualities that exist in gene...

Nowadays, analyzing human facial image has gained an ever-increasing importance due to its various applications. Image segmentation is required as a very important and fundamental operation for significant analysis and interpretation of images. Among the segmentation methods, image thresholding technique is one of the most well-known methods due to its simplicity, robustness, and high precision...

Image binarization is the process of separation of pixel values into two groups, white as background and black as foreground. Thresholding plays a major in binarization of images. Thresholding can be categorized into global thresholding and local thresholding. In images with uniform contrast distribution of background and foreground like document images, global thresholding is more appropriate....

Image segmentation is a significant technology for image process. Many segmentation methods have been brought forward to deal with image segmentation, among these methods thresholding is the simple and important one. To overcome shortcoming without using space information many thresholding methods based on 2-D histogram are often used in practical work. These methods segment images by using the...

Image entropy thresholding approach has drawn the attentions in image segmatation. The endeavor of this paper is focused on multilevel thresholding using the minimum cross enrtop criterion. In the literature, the particle swarm optimization (PSO) had been applied to conducting the thresold selection. The adopted algorithm used in this paper is the honey bee mating optimization (HBMO). In experi...

Thresholding-based techniques have been widely used in image segmentation. The selection of appropriate threshold is a very significant issue for image thresholding. In this paper, a new image histogram thresholding method based on fuzzy partition and maximum correlation criterion is presented. In the proposed approach, the regions, i.e. object and background, are considered ambiguous in nature...

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of thre...

ÐWe consider the problem of segmenting a digitized image consisting of two univariate populations. Assume a priori knowledge allows incomplete assignment of voxels in the image, in the sense that a fraction of the voxels can be identified as belonging to population 0, a second fraction to 1, and the remaining fraction have no a priori identification. Based upon estimates of the short length sca...

This paper proposes an adaptive threshold estimation method for image denoising in the wavelet domain based on the generalized Guassian distribution(GGD) modeling of subband coefficients. The proposed method called NormalShrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on subband data .The threshold is computed by βσ 2 / ...

This paper presents an optimal rnultithreshold selection algorithm for segmerttation of grey level images when objects can be distinguished by their grey level values. We dejke performance nleasures and we compare Our algorithm to others.