An Automotive Airbag Detection Method Based on Image Processing

2013 ◽  
Vol 416-417 ◽  
pp. 1350-1354 ◽  
Author(s):  
Xiang Xin Shao ◽  
Mu Jun Xie
Keyword(s):  
Image Processing ◽  
Automobile Industry ◽  
Detection Method ◽  
Detection Methods ◽  
Edge Information ◽  
Invariant Moment ◽  
Boundary Tracking ◽  
Image Edge ◽  
Auto Parts ◽  
Dial Indicator

The development of the automobile industry led to the development of auto parts, and airbags are one of the most important safety components of cars. In this paper, to meet the shortfall of traditional way of using a dial indicator to detect airbags deficiencies, a new automotive airbag shape detection methods based on image processing technology is put forward. First, extract the airbags image edge information using the method of boundary tracking, then detect whether airbags are qualified according to the similarity of image invariant moment. Experiments confirmed this method can improve the range and accuracy of the airbag detection.

scholarly journals Comparative Analysis of Image Quality Values on Edge Detection Methods

2020 ◽  
Vol 4 (2) ◽  
pp. 345-351
Author(s):  
Wicaksono Yuli Sulistyo ◽  
Imam Riadi ◽  
Anton Yudhana
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Edge Detection ◽  
Computer Technology ◽  
Detection Method ◽  
Detection Methods ◽  
Sobel Operator ◽  
Image Edge Detection ◽  
Image Edge ◽  
Edge Detection Method

Identification of object boundaries in a digital image is developing rapidly in line with advances in computer technology for image processing. Edge detection becomes important because humans in recognizing the object of an image will pay attention to the edges contained in the image. Edge detection of an image is done because the edge of the object in the image contains very important information, the information obtained can be either size or shape. The edge detection method used in this study is Sobel operator, Prewitt operator, Laplace operator, Laplacian of Gaussian (LoG) operator and Kirsch operator which are compared and analyzed in the five methods. The results of the comparison show that the clear margins are the Sobel, Prewitt and Kirsch operators, with PSNR calculations that produce values ​​above 30 dB. Laplace and LoG operators only have an average PSNR value below 30 dB. Other quality comparisons use the histogram value and the contrast value with the highest value results in the Laplace and LoG operators with an average histogram value of 110 and a contrast value of 24. The lowest histogram and contrast value are owned by the Sobel and Prewitt operators.  

scholarly journals A novel edge detection method based on efficient gaussian binomial filter

2021 ◽  
Vol 7 (2) ◽  
pp. 211
Author(s):  
El Houssain Ait Mansour ◽  
Francois Bretaudeau
Keyword(s):  
Edge Detection ◽  
High Speed ◽  
Detection Method ◽  
Detection Methods ◽  
Gaussian Filter ◽  
Image Edge Detection ◽  
Low Pass ◽  
Image Edge ◽  
Edge Detection Method ◽  
Low Pass Filters

Most basic and recent image edge detection methods are based on exploiting spatial high-frequency to localize efficiency the boundaries and image discontinuities. These approaches are strictly sensitive to noise, and their performance decrease with the increasing noise level. This research suggests a novel and robust approach based on a binomial Gaussian filter for edge detection. We propose a scheme-based Gaussian filter that employs low-pass filters to reduce noise and gradient image differentiation to perform edge recovering. The results presented illustrate that the proposed approach outperforms the basic method for edge detection. The global scheme may be implemented efficiently with high speed using the proposed novel binomial Gaussian filter.

scholarly journals A Comparison of Northern Hemisphere Atmospheric Rivers Detected by a New Image-Processing Based Method and Magnitude-Thresholding Based Methods

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 628 ◽  
Author(s):  
Guangzhi Xu ◽  
Xiaohui Ma ◽  
Ping Chang ◽  
Lin Wang
Keyword(s):  
Image Processing ◽  
North Atlantic ◽  
North Pacific ◽  
Detection Method ◽  
New Method ◽  
Detection Methods ◽  
Image Processing Algorithm ◽  
Atmospheric Rivers ◽  
The North ◽  
The North Pacific

A majority of the existing atmospheric rivers (ARs) detection methods is based on magnitude thresholding on either the integrated water vapor (IWV) or integrated vapor transport (IVT). One disadvantage of such an approach is that the predetermined threshold does not have the flexibility to adjust to the fast changing conditions where ARs are embedded. To address this issue, a new AR detection method is derived from an image-processing algorithm that makes the detection independent of AR magnitude. In this study, we compare the North Pacific and Atlantic ARs tracked by the new detection method and two widely used magnitude thresholding methods in the present day climate. The results show considerable sensitivities of the detected AR number, shape, intensities and their accounted IVT accumulations to different methods. In many aspects, ARs detected by the new method lie between those from the two magnitude thresholding methods, but stand out with a greater number of AR tracks, longer track durations, and stronger AR-related moisture transport in the AR tracks. North Pacific and North Atlantic ARs identified by the new method account for around 100–120 ×   10 3 kg/m/s IVT within the AR track regions, about 50 % more than the other two methods. This is primarily due to the fact that the new method captures the strong IVT signals more effectively.

Design of Soil-Granularity Analysis System Based on MATLAB

2015 ◽  
Vol 740 ◽  
pp. 722-726 ◽  
Author(s):  
Jian Lin Rao ◽  
Jian Shu Hou ◽  
Hao Chen ◽  
Hai Hua Li ◽  
Xue Yi Wan ◽  
...  
Keyword(s):  
Image Processing ◽  
Grain Size ◽  
Extraction Method ◽  
Detection Method ◽  
Region Of Interest ◽  
Edge Extraction ◽  
New Type ◽  
Image Edge ◽  
Analysis System ◽  
Soil Grain Size

The system in the paper based on Matlab platform. With the aid of image processing toolbox of soil image analysis and processing, the soil grain size distribution and its inclination angle can be got. It overcomes the insufficiency of the existing image edge extraction method, and proposes a new type of detection method, in order that the region of interest can be more accurately extract. The system is helpful to predict the possibility of the regional landslides.

Research on Bolt Crack Detection Method Based on Image Processing

2013 ◽  
Vol 433-435 ◽  
pp. 426-429
Author(s):  
Jin Qiu Liu ◽  
Bing Fa Zhang ◽  
Yu Zeng Wang ◽  
Guang Ya Li ◽  
Jing Ru Han
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Image Recognition ◽  
Crack Detection ◽  
Detection Method ◽  
Image Acquisition ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Contact Detection ◽  
Fracture Identification

A method of non-contact detection of bolt fracture have serial steps as follows: First of all the required data is obtained through image acquisition, then through the edge detection, image recognition and other image processing on the image to get the bolt fracture identification results, finally the non-contact measurement bolt fracture is realized. Experiments show that bolt crack detection method based on image processing, compared with the traditional detection methods improve the efficiency of detection and improve the detection accuracy. The method for bolt crack detection is feasible.

scholarly journals Quality Detection System of Transparent Nonel Tubes Based on Image Processing

2015 ◽  
Vol 9 (1) ◽  
pp. 697-702
Author(s):  
Guodong Sun ◽  
Wei Xu ◽  
Lei Peng
Keyword(s):  
Image Processing ◽  
Detection Method ◽  
Detection System ◽  
Recognition Rate ◽  
Human Vision ◽  
Detection Methods ◽  
Detection Accuracy ◽  
External Diameter ◽  
Quality Detection

The traditional quality detection method for transparent Nonel tubes relies on human vision, which is inefficient and susceptible to subjective factors. Especially for Nonel tubes filled with the explosive, missed defects would lead to potential danger in blasting engineering. The factors affecting the quality of Nonel tubes mainly include the uniformity of explosive filling and the external diameter of Nonel tubes. The existing detection methods, such as Scalar method, Analysis method and infrared detection technology, suffer from the following drawbacks: low detection accuracy, low efficiency and limited detection items. A new quality detection system of Nonel tubes has been developed based on machine vision in order to overcome these drawbacks. Firstly the system architecture for quality detection is presented. Then the detection method of explosive dosage and the relevant criteria are proposed based on mapping relationship between the explosive dosage and the gray value in order to detect the excessive explosive faults, insufficient explosive faults and black spots. Finally an algorithm based on image processing is designed to measure the external diameter of Nonel tubes. The experiments and practical operations in several Nonel tube manufacturers have proved the defect recognition rate of proposed system can surpass 95% at the detection speed of 100m/min, and system performance can meet the quality detection requirements of Nonel tubes. Therefore this quality detection method can save human resources and ensure the quality of Nonel tubes.

A Contour Tracing Algorithm for Ginseng Shape

2013 ◽  
Vol 401-403 ◽  
pp. 1268-1271
Author(s):  
Bing Quan Huo ◽  
Feng Ling Yin
Keyword(s):  
Image Processing ◽  
Computer Technology ◽  
Color Image ◽  
Binary Image ◽  
Color Information ◽  
Edge Information ◽  
Boundary Information ◽  
Image Edge ◽  
Tracing Algorithm ◽  
Neighbourhood Algorithm

More and more applications of computer technology are used in the field of agriculture. In this paper, Image processing technology is applied to ginseng shape. Get a color image from the device, remove the color information and reserve the boundary information. Highlight the image edge information by gradient sharpening, binary image and use 8-neighbourhood algorithm for tracking the border.

A PCB photoelectric image edge information detection method

Optik ◽  
2017 ◽  
Vol 144 ◽  
pp. 642-646 ◽  
Author(s):  
Fen Zhang ◽  
Naosheng Qiao ◽  
Jianfeng Li
Keyword(s):  
Detection Method ◽  
Edge Information ◽  
Image Edge ◽  
Information Detection

Research on Broken Filament Detection Method of Silk Product

2014 ◽  
Vol 716-717 ◽  
pp. 848-850
Author(s):  
Chang Niu Yang ◽  
Xing Bo Sun
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Gabor Filter ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Edge Information ◽  
Edge Detection Algorithm ◽  
Ideal Image ◽  
Image Edge ◽  
Image Edges

In this paper, we put forward a kind of adaptive edge detection algorithm of Gabor filter for silk product broken filament image. Use different directions’ Gabor filter to respectively get the broken filament image edge information. Using the method proposed in this paper to fuse the edges adaptively obtained from different directions Gabor filter, we obtain ideal image edges, and effectively eliminate the noise, also enhance the fuzzy edges at the same time. Experimental results show that the algorithm for silk products processing is effective, and the broken filament detected is clear.

Macrozooplankton Image Edge Detection Using Wavelet Packet Decomposition

2010 ◽  
Vol 108-111 ◽  
pp. 44-49
Author(s):  
Jing Ying Zhao ◽  
Hai Guo ◽  
Xing Bin Sun
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Wavelet Packet ◽  
Detection Methods ◽  
Automatic Identification ◽  
Wavelet Packet Decomposition ◽  
Edge Detectors ◽  
Reconstruction Image ◽  
Image Edge ◽  
Edge Detection Method

Comparing with the phytoplankton, there are few researches on zooplanktons. Now, many waterworks don’t monitor the zooplanktons in source water. There isn’t effective detection method for several common macro zooplanktons such as chironomid larvae, cyclops and so on, and little has been done in the field of the macro zooplanktons automatic identification and monitor. This paper puts for forward a macrozooplankton edge detection method based on wavelet packet decomposition and reconstruction. We erase the high frequency parts by applying wavelet packet decomposition in the original images and then detect the edge of reconstruction images using the common edge detectors such as Prewitt, Sobel, Roberts, Laplacian of Gaussion, Canny and so on. The experimental results show that the edge detection methods in the reconstruction image work better than in the original image.

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