The paper presents two techniques of image segmentation to facilitate image edge detection, that can be used further by image analysis based on the extracted features of image edges, Canny edge detection and Otsu thresholding are examples of the proposed techniques, the paper evaluates the effectiveness of the two methods with a variety of images, testing their suitability to natural as well as...

In this paper a novel edge detection method has been proposed which outperform Otsu method [1]. The proposed detection algorithm has been devised using the concept of genetic algorithm in spatial domain. The key of edge detection is the choice of threshold; which determines the results of edge detection. GA has been used to determine an optimal threshold over the image. Results are compared wit...

Renal biopsy image segmentation is an important step in computer-aided diagnosis. Among all available segmentation techniques, automatic thresholding methods are widely employed because of their advantages of simple implementation and time-saving. The Otsu method is one of these thresholding methods and is frequently applied in various fields. The two-dimensional (2-D) Otsu method is superior t...

Digital image segmentation based on Otsu’s method is one of the most widely used technique for threshold selection. With Otsu’s method, an optimum threshold is found by maximizing the between-class variance and the algorithm assumes that the image contains two classes of pixels or bi-modal histogram (e.g., foreground and background). It then calculates the optimal threshold value separating the...

The main objective of medical image segmentation is to extract and characterize anatomical structures with respect to some input features or expert knowledge. The Otsu method is a popular non-parametric method in medical image segmentation. Traditional Otsu method for medical image segmentation is time–consuming computation and became an obstacle in real time application systems. In the same wa...

In an effort to implement fast and effective tank segmentation from infrared images in complex background, the threshold of the maximum between-class variance method (i.e., the Otsu method) is analyzed and the working mechanism of the Otsu method is discussed. Subsequently, a fast and effective method for tank segmentation from infrared images in complex background is proposed based on the Otsu...

Xiao-Min Tong,1,2,* Predrag Ranitovic,3,4 Daniel D. Hickstein,3 Margaret M. Murnane,3 Henry C. Kapteyn,3 and Nobuyuki Toshima1 1Division of Materials Science, Faculty of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan 2Center for Computational Sciences, University of Tsukuba,1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan 3JILA and Department ...

A novel natural compound, a cycloanthranilylproline derivative (Fuligocandin B), sensitizes leukemia cells to apoptosis induced by tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) through 15-deoxy12,14 prostaglandin J2 production Hiroo Hasegawa,1,6 Yasuaki Yamada,1 Kanki Komiyama,2 Masahiko Hayashi,3 Masami Ishibashi,4 Toshiaki Sunazuka,2,3 Takeshi Izuhara,5 Kazuyuki Sugahara,1 K...

In computer vision and image processing, Otsu's method is used to automatically perform histogram shape-based image thresholding, or, the reduction of a graylevel image to a binary image. The algorithm assumes that the image to be thresholded contains two classes of pixels (e.g. for eground and background) then calculates the optimum threshold separating those two classes so that their combined...

Ant Colony Optimization (ACO) algorithms are widely used in medical imaging, especially for image edge detection and image segmentation. In this paper, fundamentally we use ACO algorithm for lung nodule detection and compare the performance against three other algorithms namely Otsu algorithm, Watershed algorithm, Global region based segmentation. In addition, we suggest a novel approach which ...