A Polynomial Algebra Approach To Binary And Gray Image Processing

1989 ◽  
Author(s):  
Prabir Bhattacharya ◽  
Kai Qian
Keyword(s):  
Image Processing ◽  
Polynomial Algebra ◽  
Gray Image ◽  
Algebra Approach

Applications of Color Morphology in Image Denoising

2014 ◽  
Vol 1037 ◽  
pp. 393-397
Author(s):  
Shui Ming He ◽  
Xue Lin Li
Keyword(s):  
Image Processing ◽  
Mathematical Morphology ◽  
Digital Image Processing ◽  
Color Image ◽  
Morphological Changes ◽  
Processing Method ◽  
Color Model ◽  
Color Image Processing ◽  
Morphological Filter ◽  
Gray Image

Mathematical morphology can be seen as a special digital image processing method and theory, which has been widely used in various fields. In this paper, the mathematical morphology is applied to the color image processing. In thespace of color image, I have simply expounded the theories and properties of color morphological changes, and defined its morphological operators. According to the application of omni-directional and multi-angle structuring elements composite morphological filter in gray image, I put forward a kind of color morphological filter with omni-directional and multi-angle structuring elements composite. This algorithm has retained its advantages in gray image, however, remaining some drawbacks. Through the optimization of results based on this algorithm, we finally get the relatively ideal denoising effects.Keywords: mathematical morphology;color model;color model; color morphological filter

scholarly journals APPLYING IMAGE PROCESSING TOOLS TO ANALYZE THE SURFACE CHARACTERISTICS OF NANO ALUMINA (NANOAL2O3) AND NANO TITANIUM (NANOTIO2)

2018 ◽  
Vol 80 (4) ◽  
Author(s):  
Abdul-Adheem Zaily Hameed ◽  
Muzhir Shaban Al-Ani ◽  
Faik Hammad Anter
Keyword(s):  
Image Processing ◽  
Composite Material ◽  
Texture Analysis ◽  
Surface Texture ◽  
Quantitative Description ◽  
Surface Characteristics ◽  
Material Surface ◽  
Mean Values ◽  
Gray Image ◽  
Nano Alumina

Composite material is a material constructed of two or more materials that leads with different physical or chemical characteristics. Nano Alumina (NANO AL2O3) and Nano Titanium (NANO TIO2) are normally used to construct the composite material. The fundamental of texture analysis seeks to derive a general efficient and compact quantitative description of textures so that various mathematical operations can be used to achieve, compare and transform of texture characteristics. Many mechanical and physical methods are used to measure the surface characteristics. Some of these methods suffered from accurate description of material surface. In addition, the details of material surface are not clear via applying the traditional methods for surface analyzing. This work is concentrated on combining many functions and steps of image processing method to understand and analyze the surface characteristics of the composite material (Nano Alumina and Nano Titanium). The implemented approach including many steps: image enhancement, texture analysis, edge detection and contour analysis. This approach leads to explain, extract, analyze and evaluate the characteristics of surface texture of the composite material via measuring of mean values for original gray image, adjusted gray image, equalized gray image and adapted gray image. The average mean values of Nano Alumina are 103, 110, 128 and 134 for the applied method respectively. The average mean values of Nano titanium are 120, 123, 125 and 129 respectively. As a conclusion the implemented approach of surface texture analysis indicated that there is a significant improvement at the surface characteristics for both equalization and adaptive methods compared with the adjustment method.

A Promotion of a Color Morphological Filter

2014 ◽  
Vol 548-549 ◽  
pp. 1064-1067
Author(s):  
Shui Ming He
Keyword(s):  
Image Processing ◽  
Mathematical Morphology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Image ◽  
Processing Method ◽  
Color Image Processing ◽  
Morphological Filter ◽  
Morphological Operators ◽  
Gray Image

Mathematical morphology can be seen as a special digital image processing method and theory, which has been widely used in various fields. In this paper, the mathematical morphology is applied to the color image processing. In thespace of color image, I have simply expounded the theories and properties of color morphological changs, and defined its morphological operators. According to the application of omni-directional and multi-angle structuring elements composite morphological filter in gray image, I put forward a kind of color morphological filter with omni-directional and multi-angle structuring elements composite. This algorithm has retained its advantages in gray image, however, remaining some drawbacks. Through the optimization of results based on this algorithm, we finally get the relatively ideal denoising effects.

scholarly journals A Computer-aided Method for Identifying the Presence of Softwood Growth Ring Boundaries

2020 ◽  
Author(s):  
Qi-Zhao Lin ◽  
Tuo He ◽  
Yong-Ke Sun ◽  
Xin He ◽  
Jian Qiu
Keyword(s):  
Image Processing ◽  
Data Analysis ◽  
Growth Ring ◽  
Threshold Value ◽  
Comparison Method ◽  
Majority Voting ◽  
Processing Technologies ◽  
Gray Image ◽  
Computer Aided ◽  
Softwood Species

ABSTRACTThe objective of this study was to develop a computer-aided method to quantify the obvious degree of growth ring boundaries of softwood species, based on data analysis with some image processing technologies. For this purpose, a 5× magnified cross-section color micro-image of softwood was cropped into 20 sub-images, then every image is binarized as a gray image according to an automatic threshold value. After that, the number of black pixels in the gray image was counted row by row and the number of black pixels was binarized to 0 or 100. Finally, a transition band from earlywood to latewood on the sub-image was identified. If this was successful, the growth ring boundaries of the sub-image are distinct, otherwise they were indistinct or absent. If 10 of the 20 sub-images are distinct, with the majority voting method, the growth ring boundaries of softwood are distinct, otherwise they are indistinct or absent. The proposed method has been visualized as a growth-ring-boundary detecting system based on the .NET Framework. A sample of 100 micro-images (Supplementary Images) of softwood cross-sections were selected for evaluation purposes. In short, this detecting system computes the obvious degree of growth ring boundaries of softwood species by image processing involved image importing, image cropping, image reading, image grayscale, image binarization, data analysis. The results showed that the method used avoided mistakes made by the manual comparison method of identifying the presence of growth ring boundaries, and it has a high accuracy of 98%.

Research on Connecting Plate Outline Measurement System Based on Image Processing

2011 ◽  
Vol 271-273 ◽  
pp. 394-398
Author(s):  
Mei Jiao Mao ◽  
Zhi Fei Tan ◽  
Shi Jie Lu
Keyword(s):  
Image Processing ◽  
Data Processing ◽  
Measurement System ◽  
Research Result ◽  
Canny Operator ◽  
Edge Information ◽  
Gray Image

This paper aims to accurately obtain connecting plate outline. First, a camera captured a connecting plate image, then transmitted it to a computer, next converted it to a gray image, after that used Canny operator to extracted its edge information, and converted the pixel points of the gray image to rectangular coordinate values, at last found out all of the vertices of the connecting plate. Research result shows that the system is simple, its accuracy is less than 0.3%, and the data processing is convenience.

Novel gray image processing in a single operation optical morphological processor

1996 ◽  
Vol 130 (1-3) ◽  
pp. 143-152 ◽  
Author(s):  
Guoliang Huang ◽  
Guofan Jin ◽  
Minxian Wu ◽  
Yingbai Yan
Keyword(s):  
Image Processing ◽  
Gray Image ◽  
Single Operation
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