The Image Processing Algorithm of Surface Topography Based on Laser Interference Measurement

In the measurement methods of microcosmic surface topography, laser interference microscopy with high precision and non-contact advantages, has been widely used. Based on the current processing algorithms of interference image, this paper studies principally the processing algorithms of single-wavelength laser interferometry and analyses the image processing algorithm of two-wavelength laser interferometry. On the basis of the original measurement precision, the two-wavelength measurement method can extend the depth measurement range and restore effectively the tested surface topography.

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Bubble Image Processing Algorithm and Application in Vacuum Casting Equipment

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.426-427.260 ◽

2010 ◽

Vol 426-427 ◽

pp. 260-264 ◽

Cited By ~ 1

Author(s):

Yuan Yuan Liu ◽

Z.F. Chi ◽

J.W. Wang ◽

Hai Guang Zhang ◽

Qing Xi Hu

Keyword(s):

Image Processing ◽

Surface Quality ◽

Manufacturing Process ◽

Casting Process ◽

Processing Algorithm ◽

Image Processing Algorithm ◽

Vacuum Casting ◽

Advantages And Disadvantages ◽

Image Processing Algorithms ◽

Processing Algorithms

Bubbles in the manufacturing process are common. The bubbles often lead to the decrease of the product’s surface quality and internal performance. This paper summarized the published researches and applications of the detection and processing for bubble images, of which the advantages and disadvantages were also presented. Based on the above mentioned results, this paper then proposed a new bubble image processing algorithm for vacuum casting process, in which the characteristics of the bubbles in vacuum casting process and the problems possibly caused in detail were analyzed. According to the characteristics of bubbles in vacuum casting process, an image processing algorithms was designed using Matlab. The simulation result showed the efficiency of the proposed algorithm.

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Realization of Image Processing Algorithm based on FPGA

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c5338.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 2882-2885

Keyword(s):

Image Processing ◽

Processing Algorithm ◽

Model Design ◽

Image Processing Algorithm ◽

Matlab Simulink ◽

System Generator ◽

Image Processing Algorithms ◽

Processing Algorithms ◽

Xilinx System Generator

This paper proposes the use of Xilinx System Generator for image processing. Several categories of algorithms are assisted by necessary libraries in Xilinx System Generator. This work integrates Matlab Simulink environment. The image processing algorithms are implemented by design approaches based on model design. The results are verified by hardware co-simulation. The system generator blocks are used for various algorithms of image processing for image negatives, RGB to grayscale, dilation, etc

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Development of Digital Image-Processing Algorithm to Compute Unified Crack Index for Salt Lake City

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198196152600118 ◽

1996 ◽

Vol 1526 (1) ◽

pp. 142-148 ◽

Cited By ~ 3

Author(s):

Siriphan Jitprasithsiri ◽

Hosin Lee ◽

Robert G. Sorcic ◽

Richard Johnston

Keyword(s):

Image Processing ◽

Digital Images ◽

Salt Lake ◽

Salt Lake City ◽

Processing Algorithm ◽

Image Processing Algorithm ◽

Crack Index ◽

Image Processing Algorithms ◽

Processing Algorithms ◽

Lake City

This paper presents the recent efforts in developing an image processing algorithm for computing a unified pavement crack index for Salt Lake City. The pavement surface images were collected using a digital camera mounted on a van. Each image covers a pavement area of 2.13 m (7 ft) × 1.52 m (5 ft), taken at every 30-m (100-ft) station. The digital images were then transferred onto a 1-gigabyte hard disk from a set of memory cards each of which can store 21 digital images. Approximately 1,500 images are then transferred from the hard disk to a compact disc. The image-processing algorithm, based on a variable thresholding technique, was developed on a personal computer to automatically process pavement images. The image is divided into 140 smaller tiles, each tile consisting of 40 × 40 pixels. To measure the amount of cracking, a variable threshold value is computed based on the average gray value of each tile. The program then automatically counts the number of cracked tiles and computes a unified crack index for each pavement image. The crack indexes computed from the image-processing algorithms are compared against the manual rating procedure in this paper. The image-processing algorithms were applied to process more than 450 surveyed miles of Salt Lake City street network.

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Human Activity Classification for Surveillance using Machine Learning and Image Processing Algorithm

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v7i6.343346 ◽

2019 ◽

Vol 7 (6) ◽

pp. 343-346

Author(s):

Arvind Malge ◽

Mallikarjuna Shastry P.M

Keyword(s):

Machine Learning ◽

Image Processing ◽

Human Activity ◽

Processing Algorithm ◽

Image Processing Algorithm ◽

Activity Classification

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Design of an Automatic Light Intensity Control System and Image Processing Algorithm for the Development of an Assistive Drug Screening Device

SSRN Electronic Journal ◽

10.2139/ssrn.3472593 ◽

2019 ◽

Author(s):

John Louis Cruz ◽

Edryl Aljecera ◽

Arlenvy Ayson ◽

Dennis Jefferson Amora ◽

Shearyl Arenas ◽

...

Keyword(s):

Image Processing ◽

Control System ◽

Light Intensity ◽

Drug Screening ◽

Processing Algorithm ◽

Image Processing Algorithm ◽

Intensity Control ◽

Screening Device

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Image processing algorithm of computer-aided diagnosis in lung cancer screening by CT

Systems and Computers in Japan ◽

10.1002/scj.20156 ◽

2005 ◽

Vol 36 (7) ◽

pp. 40-53 ◽

Cited By ~ 2

Author(s):

Shinji Yamamoto

Keyword(s):

Lung Cancer ◽

Image Processing ◽

Cancer Screening ◽

Lung Cancer Screening ◽

Computer Aided Diagnosis ◽

Processing Algorithm ◽

Image Processing Algorithm ◽

Computer Aided ◽

Aided Diagnosis

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Internal quality evaluation of chestnut using nuclear magnetic resonance

International Journal of Food Engineering ◽

10.1515/ijfe-2019-0389 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Soo Hyun Park ◽

Sang Ha Noh ◽

Michael J. McCarthy ◽

Seong Min Kim

Keyword(s):

Image Processing ◽

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Processing Algorithm ◽

Internal Quality ◽

Soluble Solid Content ◽

Mr Images ◽

Image Processing Algorithm ◽

Internal Defects ◽

Nuclear Magnetic

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

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