Forensic Detection of Median Filtering by Hough Transform of Digital Image

2017 ◽  
Author(s):  
Jae Jeong Hwang ◽  
Kang Hyeon Rhee
Keyword(s):  
Digital Image ◽  
Hough Transform ◽  
Median Filtering

Realization of Car’s Frontal Projected Area Based on OpenCV

2013 ◽  
Vol 300-301 ◽  
pp. 1673-1676 ◽  
Author(s):  
Chun Bo Dong ◽  
Xing Jun Hu ◽  
Yan Wang ◽  
Li Min Fu
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
High Accuracy ◽  
Median Filtering ◽  
Contour Extraction ◽  
Projected Area ◽  
Automotive Body ◽  
Body Development ◽  
Image Processing Algorithms

Digital image processing technology applied to the field of automotive body development, especially the aerodynamic development of the external shape of automobile. This method and its corresponding software improve the efficiency compared with other traditional fluid software tools in processing the car’s front area, reduce artificial error, and have high accuracy. Digital image processing algorithms used in this article includes Image Gray, Median Filtering, Image Segmentation, Contour Extraction and so on.

A NEWLY MODIFIED ALGORITHM OF HOUGH TRANSFORM FOR LINE DETECTION

2005 ◽  
Vol 05 (04) ◽  
pp. 715-727
Author(s):  
QIANG WANG ◽  
HONGBO CHEN ◽  
XIAORONG XU ◽  
HAIYAN LIU
Keyword(s):  
Computational Complexity ◽  
Digital Image ◽  
Hough Transform ◽  
Experimental Results ◽  
Line Detection ◽  
Storage Requirement ◽  
Heavy Burden ◽  
Modified Algorithm ◽  
Better Than

The heavy burden of computational complexity and massive storage requirement is the drawback of the standard Hough transform (SHT). To overcome the weakness of SHT, many modified approaches, for example, the probabilistic Hough transform (PHT), have been presented. However, a very important fact, which is that a line has its own width in a real digital image and the width of the line is uniform, was ignored by all of these modified algorithms of Hough transform. This phenomenon influenced the result of line detection. In this paper a new modified algorithm of Hough transform for line detection is proposed. In our algorithm, the fact mentioned above is fully considered and a strip-shaped area corresponding to the accumulate cells of HT is proposed. Experimental results have shown that our approach is efficient and promising, and the effect of detection is far better than the popular modified approaches.

Applied-Information Technology with Method of Digital Image Noise Processing

2014 ◽  
Vol 951 ◽  
pp. 253-256 ◽  
Author(s):  
Guo Qing Yu ◽  
Chen Meng Sui ◽  
Bing Dong Sui
Keyword(s):  
Image Processing ◽  
Information Technology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Average Method ◽  
Image Noise ◽  
Computer Algorithm ◽  
Basic Knowledge ◽  
Median Filtering ◽  
Low Pass

Digital image processing is a kind of technology which employs a certain algorithm to realize image processing through computer algorithm. The powerful capacity of computing and graphics displaying function of Matlab makes image processing becomes more simple and intuitive. This paper introduces the basic knowledge of dealing with noise in digital image, expounds the neighborhood average method, median filtering in detail, and low pass filtering and other typical of eliminating noise method , and at the same time analyzes and compares the characteristics of several typical methods by use of the software Matlab.

A Survey on Various Median Filtering Techniques For Removal of Impulse Noise From Digital Image

2018 ◽  
Author(s):  
Ginu George ◽  
Rinoy Mathew Oommen ◽  
Shani Shelly ◽  
Stephie Sara Philipose ◽  
Ann Mary Varghese
Keyword(s):  
Digital Image ◽  
Impulse Noise ◽  
Median Filtering ◽  
Filtering Techniques

An Automatic Microalgal Cells Counting Method

2014 ◽  
Vol 1010-1012 ◽  
pp. 178-181
Author(s):  
Yun Zhao ◽  
De Jian Zheng ◽  
Ying Shen
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Binary Image ◽  
Morphological Operations ◽  
Microscopic Image ◽  
Median Filtering ◽  
Counting Method ◽  
Automatic Counting

An automatic counting method for microalgal cells were proposed using digital image processing with characteristics of microalgae microscopic image considered. Firstly, the microalgae image was pretreated with graying, and was then applied the median filtering to remove the noise. Secondly, the image was applied Bot-hat conversion to enhance the contrast. Thirdly, the image was segmented with Otsu algorithm, and was then applied morphological operations. Finally, the binary image segments representing microalgal cells were labeled and counted. The results of experiments showed that this method was simple, efficient and accurate in counting microalgal cells in the microscopic image.

The Median Filtering of Digital Image Based on MATLAB

2013 ◽  
Vol 318 ◽  
pp. 67-70 ◽  
Author(s):  
Hai Qiang Wang ◽  
Xian Ge Sun
Keyword(s):  
Image Processing ◽  
Adaptive Filter ◽  
Digital Image ◽  
Nonlinear Filtering ◽  
Noise Intensity ◽  
Median Filter ◽  
Low Noise ◽  
Median Filtering ◽  
Filtering Method ◽  
Filtering Technique

In the processing of image de-noising, median filtering is a more common nonlinear filtering technique. In this paper, we used the image processing toolbox in the matlab and the adaptive filter program by ourselves. The noise in different intensity of image is reduced. This paper discussed the problem that how we choice of the filtering method under different noise intensity. The results show that median filter can realize effective filter under low noise intensity, if the noise intensity is excessively large, the adaptive filter having a more ideal filtering result than that of standard median filter.

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