Air Quality Evaluation Based on Local Normalized Image Contrast

2014 ◽  
Vol 511-512 ◽  
pp. 413-416 ◽  
Author(s):  
Wen Ming Yang ◽  
Xiang Chen ◽  
Qing Min Liao
Keyword(s):  
Image Processing ◽  
Air Quality ◽  
Digital Image ◽  
Quality Evaluation ◽  
Image Contrast ◽  
Experimental Results ◽  
Image Blurring ◽  
Pm2.5 And Pm10

Air quality has been paid increasingly attention, and air quality evaluation via digital image technology can help people know the air quality conveniently. Visible pollutants can affect the degree of image blurring, so it is possible to evaluate the density of these pollutants using image processing. We adopt a local normalized image contrast and attempt to explore its relationship with the values of PM2.5 and PM10. Experimental results demonstrate the proposed measure is promising.

Air Quality Evaluation Based on Image Defogging

2014 ◽  
Vol 513-517 ◽  
pp. 3077-3080
Author(s):  
Wen Ming Yang ◽  
Xiang Chen ◽  
Qing Min Liao
Keyword(s):  
Image Processing ◽  
Standard Deviation ◽  
Air Quality ◽  
Digital Image Processing ◽  
Digital Image ◽  
Quality Evaluation ◽  
New Method ◽  
Image Defogging ◽  
Dark Channel ◽  
Excellent Method

Air quality evaluation based on digital image processing is an innovative and promising matter. The density of fog and haze can reflect air quality, therefore we introduce a new method for air quality evaluation via image defogging technology. Dark channel, proposed in [, is an excellent method to remove fog and haze. Using dark channel, we can acquire transmission map of an image, and transmission map contains the information of fog and haze's density, therefore, SDT(standard deviation of transmission) is adopted as a measure in this paper.

Color Features and Color Spaces Applications to the Automatic Image Annotation

Biometrics ◽  
2017 ◽  
pp. 1061-1083
Author(s):  
Vafa Maihami ◽  
Farzin Yaghmaee
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Image Annotation ◽  
Color Histogram ◽  
Experimental Results ◽  
Automatic Image Annotation ◽  
Color Spaces ◽  
Color Features ◽  
Different Color ◽  
Color Moment

Nowadays images play a crucial role in different fields such as medicine, advertisement, education and entertainment. Describing images content and retrieving them are important fields in image processing. Automatic image annotation is a process which produces words from a digital image based on the content of this the image by using a computer. In this chapter, after an introduction to neighbor voting algorithm for image annotation, we discuss the applicability of color features and color spaces in automatic image annotation. We discuss the applicability of three color features (color histogram, color moment and color Autocorrelogram) and three color spaces (RGB, HSI and YCbCr) in image annotation. Experimental results, using Corel5k benchmark annotated images dataset, demonstrate that using different color spaces and color features helps to select the best color features and spaces in image annotation area.

scholarly journals Quality Evaluation of Melinjo Seeds (Gnetum gnemon L.)Using Digital Image Processing

2018 ◽  
Vol 7 (2) ◽  
pp. 106 ◽  
Author(s):  
Slamet Widodo ◽  
Muhammad Kalili
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Quality Evaluation ◽  
Seed Extract ◽  
Raw Material ◽  
Key Factors ◽  
Gnetum Gnemon ◽  
Lighting Systems

Some studies show that melinjo (Gnetum gnemon L.) seed extract contains various active ingredients that are beneficial to human health; even it has been commercialized as a health supplement product. Quality of seeds as raw material becomes one of key factors that determine the quality of product derived from melinjo seed extract. Therefore sorting becomes a critical process. However the sorting of good quality and broken seeds (moldy, chalky and perforated/infected insects) is still done manually with visual observations that tend to be inaccurate and inconsistent. This study aims to develop a new method for evaluation of quality of melinjo seeds based on digital image processing. The image is taken using two lighting systems i.e. frontlight and backlight. The results show that using color features (RGB and HSV) and certain threshold values, good quality and broken seeds can be distinguished by 92.5% and 100% accuracy using frontlight and backlight image respectively. It indicates that digital image processing can be used as an alternative for quality evaluation of melinjo seed.

A Self-Environment Adaption Model for Cross-Media Reproduction of Digital Image

2012 ◽  
Vol 262 ◽  
pp. 134-137
Author(s):  
Xiang Yang Xu ◽  
Li Jie Wang ◽  
Qiao Chen
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Image Display ◽  
Experimental Results ◽  
Ambient Light ◽  
Cross Media ◽  
Color Conversion

A self- environment adaption model for cross-media reproduction of digital image is presented in this paper.This model is used to color conversion, makes image adaptive display according to ambient light changes. Experimental results show that this model can be used in all kinds of image processing systems for the displaying of image, particularly suitable for handheld image display apparatus.

The Algorithm to Measure Crack Width with Incircle

2013 ◽  
Vol 684 ◽  
pp. 481-485 ◽  
Author(s):  
Bao Zhen Ge ◽  
Qi Jun Luo ◽  
Bin Ma ◽  
Yong Jie Wei ◽  
Bo Chen ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Crack Width ◽  
Experimental Results ◽  
Average Width ◽  
Center Of A Group ◽  
Major Defect ◽  
Skeleton Point

Crack is a major defect of buildings. Digital image methods are often used to detect cracks. But incorrect or un-unique results may be inverted with an inappropriate algorithm. An image processing way is presented to obtain the sole width value. Meanwhile, the crack with several branches can be measured. In the processing, the crack skeleton is first calculated. Then each of the points on the skeleton is served as a center of a group of circles, one by one. The radius of the circles is increased step by step. The iterations will not stop until any point in the circle goes out of the crack. Thus the last circle in the iteration is served as an incircle of the crack. The diameter of the incircle is a crack width in a given skeleton point. The maximal and average width of the crack will be calculated after all the incircles with all the skeleton point are traversed. The experimental results show the proposed method can extract the width of cracks in a complex context.

Color Features and Color Spaces Applications to the Automatic Image Annotation

2016 ◽  
pp. 378-400 ◽  
Author(s):  
Vafa Maihami ◽  
Farzin Yaghmaee
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Image Annotation ◽  
Color Histogram ◽  
Experimental Results ◽  
Automatic Image Annotation ◽  
Color Spaces ◽  
Color Features ◽  
Different Color ◽  
Color Moment

Nowadays images play a crucial role in different fields such as medicine, advertisement, education and entertainment. Describing images content and retrieving them are important fields in image processing. Automatic image annotation is a process which produces words from a digital image based on the content of this the image by using a computer. In this chapter, after an introduction to neighbor voting algorithm for image annotation, we discuss the applicability of color features and color spaces in automatic image annotation. We discuss the applicability of three color features (color histogram, color moment and color Autocorrelogram) and three color spaces (RGB, HSI and YCbCr) in image annotation. Experimental results, using Corel5k benchmark annotated images dataset, demonstrate that using different color spaces and color features helps to select the best color features and spaces in image annotation area.

Local Statistic Enhancement of Digital Image Based on Genetic Algorithm

2013 ◽  
Vol 427-429 ◽  
pp. 1836-1840 ◽  
Author(s):  
Yong Zhuo Wu ◽  
Zhen Tu ◽  
Lei Liu
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Experimental Results ◽  
Computer Application ◽  
Novel Method ◽  
New Research

Iamge repair using the digital image processing technology has become a new research point in computer application. A novel method of local statistic enhancement based on genetic algorithm is proposed in this paper for the image enhancement. The modified amplified function are used as the jugement criterion, and the optimal paremeters are searched by the genetic algorithm. Experimental results show that the quality of images is improved dramatically by using this method.

scholarly journals DIGITAL IMAGE PROCESSING AND RECOGNITION USING PYTHON

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
D. Sri Shreya
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Face Recognition ◽  
Digital Image Processing ◽  
Digital Image ◽  
Gaussian Function ◽  
Numerical Data ◽  
Input Image ◽  
Image Blurring ◽  
Learning Concept

In this project, the primary aim will be the conversion of images into Grayscale in which conversion of pixels to array takes place and apply Blur effect using The Gaussian blur which is a type of image-blurring filter that uses a Gaussian function which also expresses the normal distribution in statistics for calculating the transformation to apply to each pixel in the image. The above two processesare applied to the input images. These two above mentioned processes can be achieved by utilizing the most relevant python libraries and functions, followed by conversion of the digital image to numerical data and then, applying the effects to the image to get back the image with applied effects in it. Face recognition refers to matching a face present in an input image from the training/pre-saved dataset and by applying Deep Learning Concept. This will be achieved by defining a function to read and convert images to data, apply the python function, and then, recreating the image with results.

scholarly journals Mobile Application Detection of Road Damage using Canny Algorithm

2018 ◽  
Author(s):  
Andysah Putera Utama Siahaan ◽  
Janner Simarmata ◽  
Robbi Rahim
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Mobile Application ◽  
Experimental Results ◽  
Threshold Function ◽  
The Road ◽  
Canny Algorithm ◽  
Crack Paths

Edge detection is one of the most frequent processes in digital image processing for various purposes, one of which is detecting road damage based on crack paths that can be checked using a Canny algorithm. This paper proposed a mobile application to detect cracks in the road and with customized threshold function in the requests to produce useful and accurate edge detection. The experimental results show that the use of threshold function in a canny algorithm can detect better damage in the road.

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

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