Fast and Direct Polygonization for Gray-Scale Images Using Digital Straightness and Exponential Averaging

2016 ◽  
Vol 16 (02) ◽  
pp. 1650007
Author(s):  
Sanjoy Pratihar ◽  
Partha Bhowmick
Keyword(s):  
Digital Image ◽  
Experimental Results ◽  
Gray Scale ◽  
Gray Scale Image ◽  
Improved Algorithm

Although there exist various algorithms for polygonization of objects present in a digital image, most of them cannot directly be applied on a gray-scale image without resorting to edge map computation, thinning, etc. Hence, with the aim of applying polygonization directly on a gray-scale image, we propose here an improved algorithm. It is based on a novel proposition of exponential averaging of estimated edge strengths, which is used to extract (thinned) digitally straight edges directly from a gray-scale image. These straight edges are subsequently used as input for a fast polygonization based on simple primitive operations in the integer domain. Procedural advantages and implementation details of the proposed method are explained in this paper to adjudge its fitness in the context of polygonization. Experimental results have been furnished to demonstrate the usefulness, efficiency, and robustness of the proposed technique.

scholarly journals Analysis of the Cluster Prominence Feature for Detecting Calcifications in Mammograms

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Alejandra Cruz-Bernal ◽  
Martha M. Flores-Barranco ◽  
Dora L. Almanza-Ojeda ◽  
Sergio Ledesma ◽  
Mario A. Ibarra-Manzano
Keyword(s):  
Digital Image ◽  
Visual Inspection ◽  
Experimental Results ◽  
Gray Scale ◽  
High Expectation ◽  
Weak Classifier ◽  
White Region ◽  
Gray Scale Image ◽  
Global Representation

In mammograms, a calcification is represented as small but brilliant white region of the digital image. Earlier detection of malignant calcifications in patients provides high expectation of surviving to this disease. Nevertheless, white regions are difficult to see by visual inspection because a mammogram is a gray-scale image of the breast. To help radiologists in detecting abnormal calcification, computer-inspection methods of mammograms have been proposed; however, it remains an open important issue. In this context, we propose a strategy for detecting calcifications in mammograms based on the analysis of the cluster prominence (cp) feature histogram. The highest frequencies of the cp histogram describe the calcifications on the mammography. Therefore, we obtain a function that models the behaviour of the cp histogram using the Vandermonde interpolation twice. The first interpolation yields a global representation, and the second models the highest frequencies of the histogram. A weak classifier is used for obtaining a final classification of the mammography, that is, with or without calcifications. Experimental results are compared with real DICOM images and their corresponding diagnosis provided by expert radiologists, showing that the cp feature is highly discriminative.

A New Approach for Gray Image Segmentation Using Level Set Method

2014 ◽  
Vol 530-531 ◽  
pp. 372-376 ◽  
Author(s):  
Lai Zhen Li ◽  
Shuai Han ◽  
Wen Ming Wang ◽  
Hu Tan ◽  
Qiang Zhou
Keyword(s):  
Image Segmentation ◽  
Level Set Method ◽  
Level Set ◽  
Small Area ◽  
Experimental Results ◽  
Curve Evolution ◽  
Gray Scale ◽  
New Approach ◽  
A Value ◽  
Gray Scale Image

The techniques and the processes to divide the image into several parts which have different features and to pick up foreground are called image segmentation. In this work, we propose a new approach for gray scale image segmentation based on level set method. At first, every pixel on the image is divided into either similar-property class or dissimilar-property class based on the variance of a small area centered at the pixel. Then, the velocity of curve evolution for these two classes is defined respectively. It is determined by a value called the dissimilarity of the area. Experimental results show that this approach can obtain good segmentation results of artificial images and real medical images fast and accurately.

Design and Implementation of Spurs Detection System Based on OpenCV

2011 ◽  
Vol 345 ◽  
pp. 217-222
Author(s):  
Peng He ◽  
Lian Peng Wang ◽  
Na Wang ◽  
Gang Xu
Keyword(s):  
Computed Tomography ◽  
Embedded System ◽  
Detection System ◽  
Experimental Results ◽  
Design And Implementation ◽  
Function Expansion ◽  
The Embedded System ◽  
Improved Function ◽  
Small Bone ◽  
Improved Algorithm

In order to better solve the problem of detection of small bone spurs with convenient and accurate way, a portable spur detection system is designed. This system, in view of spur reproducibility characteristic, is characterized by the application for a kind of the improved algorithm based on the OpenCV. And it was successfully transplanted into the embedded system. The experimental results indicated that this system might precisely examine the small spur with difficulty discovery by naked eyes used fully by two images of computed tomography which done in different periods. The spur detection system needs to be further improved function to realize more applications. In fact, function expansion based on the system is easy to realize.

Blind Digital Image Watermarking Algorithm Based on the Chain Code

2012 ◽  
Vol 546-547 ◽  
pp. 410-415
Author(s):  
Chun Ge Tang ◽  
Tie Sheng Fan ◽  
Lei Liu ◽  
Zhi Hui Li
Keyword(s):  
Image Quality ◽  
Digital Watermarking ◽  
Digital Image ◽  
Image Watermarking ◽  
Boundary Representation ◽  
Experimental Results ◽  
Digital Image Watermarking ◽  
Original Image ◽  
Chain Code ◽  
Decision Method

A new blind digital watermarking algorithm based on the chain code is proposed. The chain code is obtained by the characteristics of the original image -the edge contour. The feather can reflect the overall correlation of the vector image, and chain code expression can significantly reduce the boundary representation of the amount of data required. For the watermarking embedding, the original vector image is divided into sub-block images, and two bits of the watermarking information are embedded into sub-block images repeatedly by quantization. For watermarking extracting, the majority decision method is employed to determine the size of the extracted watermark. Experimental results show that the image quality is not significantly lowered after watermarking. The algorithm can resist the basic conventional attacks and has good robustness on the shear attacks.

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