Quality analysis using three-dimensional modelling and image processing techniques

2019 ◽  
Vol 19 (4) ◽  
pp. 614-628 ◽  
Author(s):  
Mohamed Marzouk ◽  
Mahmoud Hassouna
Keyword(s):  
Image Processing ◽  
3D Model ◽  
Median Filter ◽  
Mean Shift ◽  
Three Dimensional ◽  
Wiener Filter ◽  
Quality Analysis ◽  
Split Bregman ◽  
Specific Element ◽  
Content Type

Purpose This paper aims to propose a system for defect detection in constructed elements that is able to indicate deformity positions. It also evaluates the defects in finishing materials of constructed building elements to support the subjective visual quality investigation of the aesthetics of an architectural work. Design/methodology/approach This strategy depends on defect features analysis that evaluates the defect value in digital images using digital image processing methods. The research uses the three-dimensional (3D) modeling techniques and image processing algorithms to generate a system that is able to perform some of the monitoring activities by computers. Based on the collected site scans, a 3D model is created for the building. Then, several images can be exported from the 3D model to investigate a specific element. Different image denoizing techniques are compared such as mean filter, median filter, Wiener filter and Split–Bregman iterations. The most efficient technique is implemented in the system. Then, the following six different methods are used for image segmentation to separate the concerned object from the background; color segmentation, region growing segmentation, histogram segmentation, local standard deviation segmentation, adaptive threshold segmentation and mean-shift cluster segmentation. Findings The proposed system is able to detect the cracks and defected areas in finishing works and calculate the percentage of the defected area compared to the total captured area in the photo with high accuracy. Originality/value The proposed system increases the precision of decision-making by decreasing the contribution of human subjective judgment. Investigation of different finishing surfaces is applied to validate the proposed system.

Comparative Analysis on Noise Processing of Image

2013 ◽  
Vol 718-720 ◽  
pp. 2159-2162
Author(s):  
Hua Jun Dong ◽  
Xue Mei Jiang ◽  
Chen Xu Niu
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
Median Filter ◽  
Wiener Filter ◽  
Image Noise ◽  
Two Dimensional ◽  
Wavelet Filter ◽  
Average Filter

The existence of noises have great interference on image processing, so the elimination of image noise is of great importance. In this paper, based on the digital image processing, the methods of average filter, wiener filter, median filter, two-dimensional wavelet filter, maximum and minimum filter are used to eliminate the salt & pepper noise of image. Then we analysis and compare the results of the five methods to find the best way to eliminate the image noise.

Models partition for 3D printing objects using skeleton

2017 ◽  
Vol 23 (1) ◽  
pp. 54-64 ◽  
Author(s):  
Xiaotong Jiang ◽  
Xiaosheng Cheng ◽  
Qingjin Peng ◽  
Luming Liang ◽  
Ning Dai ◽  
...  
Keyword(s):  
3D Model ◽  
Three Dimensional ◽  
Principal Component ◽  
3D Models ◽  
Sweep Method ◽  
Final Model ◽  
Content Type ◽  
Working Volume ◽  
Minima Rule ◽  
The Greedy Algorithm

Purpose It is a challenge to print a model with the size that is larger than the working volume of a three-dimensional (3D) printer. The purpose of this paper is to present a feasible approach to divide a large model into small printing parts to fit the volume of a printer and then assemble these parts into the final model. Design/methodology/approach The proposed approach is based on the skeletonization and the minima rule. The skeleton of a printing model is first extracted using the mesh contraction and the principal component analysis. The 3D model is then partitioned preliminarily into many smaller parts using the space sweep method and the minima rule. The preliminary partition is finally optimized using the greedy algorithm. Findings The skeleton of a 3D model can effectively represent a simplified version of the geometry of the 3D model. Using a model’s skeleton to partition the model is an efficient way. As it is generally desirable to have segmentations at concave creases and seams, the cutting position should be located in the concave region. The proposed approach can partition large models effectively to well retain the integrity of meaningful parts. Originality/value The proposed approach is new in the rapid prototyping field using the model skeletonization and the minima rule. Based on the authors’ knowledge, there is no method that concerns the integrity of meaningful parts for partitioning. The proposed method can achieve satisfactory results by the integrity of meaningful parts and assemblability for most 3D models.

Ultrasonic Image Processing Using a Three-Dimensional Median Filter

1991 ◽  
Vol 30 (S1) ◽  
pp. 228 ◽  
Author(s):  
Takashi Mochizuki ◽  
Masayasu Ito ◽  
Kenkichi Tachikawa
Keyword(s):  
Image Processing ◽  
Median Filter ◽  
Three Dimensional ◽  
Ultrasonic Image

Ceramic Microstructure Image Segmentation by Mean Shift

2013 ◽  
Vol 423-426 ◽  
pp. 2602-2605 ◽  
Author(s):  
Hua Hui Cai ◽  
Yan Cheng ◽  
Bing Xiang Liu
Keyword(s):  
Image Processing ◽  
Median Filter ◽  
Mean Shift ◽  
Segmentation Algorithm ◽  
Electronic Noise ◽  
Microscopic Image ◽  
Mean Shift Clustering ◽  
Ceramic Microstructure ◽  
The Mean ◽  
Microscopic Image Processing

In order to effectively assist the researchers conduct quantitative analysis of ceramic microstructures, a segmentation algorithm based on mean shift is used for the ceramic microstructure image. Since the collection and transfer process of microscopic image will inevitably be subject to uneven distribution of light, electronic noise and other interference factors which make the image quality deterioration, it is necessary to reduce noises and enhance edges for ceramic microscopic image processing at first. Therefore, the median filter is used to remove the noises in the ceramic microstructure images. Then the component with similar feature is separated and merged by the mean shift segmentation algorithm. Experiments show the proposed algorithm of using median filter and mean shift clustering gives satisfactory results.

scholarly journals Comparative Image Quality Analysis of Spatial Filters for Pre-processing of CT Abdominal Images

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 1449-1469
Author(s):  
Ramya Mohan ◽  
S.P. Chokkalingam ◽  
Kirupa Ganapathy ◽  
A. Rama
Keyword(s):  
Image Processing ◽  
Gaussian Noise ◽  
Median Filter ◽  
Wiener Filter ◽  
Speckle Noise ◽  
Ct Images ◽  
Spatial Filters ◽  
Abdominal Ct ◽  
Wiener Filters ◽  
Salt And Pepper

Aim: To determine the efficient noise reduction filter for abdominal CT images. Background: Image enrichment is the first and foremost step that has to be done in all image processing applications. It is used to enhance the quality of digital images. Digital images are liable to addition of noise from various sources such as error in instrument calibration, excess staining of images, etc., Image de-noising is an enhancement technique used to remove / reduce noise present in an image. Reducing the noise of images and preserving its edges are always critical and challenging in image processing. Materials and Method: In this paper, four different spatial filters namely Mean, Median, Gaussian and Wiener were used on 100 CT abdominal images and their performances were compared against the following four parameters: Peak signal to noise ratio (PSNR), Mean Square Error (MSE), Normalised correlation coefficient (NCC) and Normalised Absolute Error (NAE) to determine the best denoising filter for the abdominal CT images. Result: Based on the experimental parameters, the median filter had the maximum efficiency in managing salt and pepper noise than the other three filters. Both Median and Wiener filters showed efficiency in removing the Gaussian noise. Whereas, the Wiener filter demonstrated higher efficiency in reducing both Poisson and Speckle noise. Conclusion: Based on the results of this study, we can conclude that the median filter can be used to reduce Salt and Pepper noises. Median and Wiener filters are significantly better for Gaussian Noise and the Wiener filter can be used to reduce both Poisson & Speckle noise in abdominal CT images.

scholarly journals 3D textile reconstruction based on KinectFusion and synthesized texture

2017 ◽  
Vol 29 (6) ◽  
pp. 793-806 ◽  
Author(s):  
PengPeng Hu ◽  
Taku Komura ◽  
Duan Li ◽  
Ge Wu ◽  
Yueqi Zhong
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
3D Model ◽  
Three Dimensional ◽  
Experimental Results ◽  
High Quality ◽  
Content Type

Purpose The purpose of this paper is to present a novel framework of reconstructing the 3D textile model with synthesized texture. Design/methodology/approach First, a pipeline of 3D textile reconstruction based on KinectFusion is proposed to obtain a better 3D model. Second, “DeepTextures” method is applied to generate new textures for various three-dimensional textile models. Findings Experimental results show that the proposed method can conveniently reconstruct a three-dimensional textile model with synthesized texture. Originality/value A novel pipeline is designed to obtain 3D high-quality textile models based on KinectFusion. The accuracy and robustness of KinectFusion are improved via a turntable. To the best of the authors’ knowledge, this is the first paper to explore the synthesized textile texture for the 3D textile model. This is not only simply mapping the texture onto the 3D model, but also exploring the application of artificial intelligence in the field of textile.

Performance Analysis of Several Common Filter

2012 ◽  
Vol 220-223 ◽  
pp. 1446-1449
Author(s):  
Hai Bo Jiang ◽  
Jing Zhi Cai
Keyword(s):  
Image Processing ◽  
Kalman Filter ◽  
Performance Indicators ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Wiener Filter ◽  
Paper Analysis ◽  
Signal To Noise ◽  
Initial Stage ◽  
Average Filter

Denoising is the initial stage of image processing, in preparation for the subsequent processing of the image. This article describes a field of several denoising used filters include average filter, median filter, Wiener filter, Kalman filter. Combination of diagrams, will describe their filtering principle, at the end of this paper,analysis signal to noise ratio of image and other performance indicators .

Fabrication of 3D microfluidic structure with direct selective laser baking of PDMS

2019 ◽  
Vol 25 (4) ◽  
pp. 775-780 ◽  
Author(s):  
Mohammadreza Riahi ◽  
Fatemeh Karimi ◽  
Atefeh Ghaffari
Keyword(s):  
3D Printing ◽  
Design Methodology ◽  
3D Model ◽  
Three Dimensional ◽  
Laser Irradiance ◽  
Curing Time ◽  
Content Type ◽  
3D Print ◽  
Dimethyl Siloxane ◽  
Baking Process

Purpose The purpose of this paper is to present three-dimensional (3D) printing of structures with a new method called selective laser baking (SLB) of Poly Dimethyl Siloxane (PDMS). Design/methodology/approach A 3D model is designed on the computer. PDMS Base is mixed with its hardener and poured into a container. Before it is hardened which normally occures after several hours, a CO2 laser selectively exposes different areas on the surface of the PDMS mixture according to the pattern of a slice of a 3D model designed on the computer. Because of the thermal effect of the CO2 laser, once exposed, PDMS heats up and hardens, producing a cured layer of PDMS which is attached to a base. The base with the cured layer is lowered in the container for a short distance and a layer of new uncured PDMS is spread over the previous layer. The laser exposes new areas again and hardens them. This process is repeated until the whole structure is fabricated. Findings The parameters involved in the baking process are investigated and the relation between temperature, mixing portion and laser irradiance on the curing time and layer thickness are investigated. Originality/value This fabrication technique is a unique fabrication method that helps to 3D print with two base polymers which their polymerization can be boosted by heat. This 3D printing method has not been presented earlier.

scholarly journals Removal of various Noises in Dental X-ray Images using Selective Median Filter

2019 ◽  
Vol 8 (12) ◽  
pp. 2550-2558
Keyword(s):  
Image Processing ◽  
Gaussian Noise ◽  
Median Filter ◽  
Medical Image Analysis ◽  
Wiener Filter ◽  
Speckle Noise ◽  
Linear Filters ◽  
Severe Problem ◽  
X Ray ◽  
Non Linear

Image processing plays major role to provide additional information in medical diagnosis. Input images contain picture information as well as noise information. Noise information is added with the images during signal acquisition stage or in the transmission of image data. Salt & Pepper noise, Gaussian noise and Speckle noise is the major noises introduced in the images. Noise information may be interpreted as data and it may lead to severe problem. Linear and Non-linear filters are used to reduce these noises in the images. In medical image analysis, non-linear filters are preferred over linear filters because it preserves edge information. Dental X-ray image is used to identify the cavities and its depth. Average filter, median filter and wiener filter are the classical techniques used in many image processing applications. In this paper, three different noises (Salt &pepper, Gaussian and Speckle noise) are added and different filters (Average filters, median filter, Wiener filter) performances are analysed with the PSNR, SNR and MSE. Analysis shows that median filter is suitable for reducing salt & pepper noise and wiener filter is suitable for reducing Gaussian noise and speckle noise in the dental x-ray images. Selective median filter is a modified wiener filter. Median filter is used for the pixel value 0 and 255.For other pixel values wiener filter is used. Selective median filter is giving better result than traditional techniques

scholarly journals A quality analysis method for three-dimensional model in aircraft structural parts design

2021 ◽  
Vol 13 (3) ◽  
pp. 168781402110080
Author(s):  
Kai Wang ◽  
Ning Zhao ◽  
Qiang He ◽  
Jianxin Xu
Keyword(s):  
Index System ◽  
Process Model ◽  
3D Model ◽  
Three Dimensional ◽  
Assessment Model ◽  
Quality Analysis ◽  
Test Model ◽  
Fuzzy Synthetic Evaluation ◽  
Structural Parts ◽  
Synthetic Evaluation

To analyze the quality of three-dimensional (3D) model for aircraft structural parts designed by model-based definition (MBD) technology, an approach combining analytic hierarchy process (AHP), hesitant fuzzy linguistic term set (HFLTS), and fuzzy synthetic evaluation is proposed. According to all levels of quality standards and part specification-tree elements, a quality assessment index system is constructed from four sub-models of parts 3D model: design model, process model, tooling model, and test model. In addition, the weight of each index is calculated using the AHP. Then the assessment model is established by using a configurable index system model, HFLTS, fuzzy synthetic evaluation, and assigning uniformly and quantitatively the index system through quality grade division rules of indexes and triangular fuzzy numbers. Finally, a case application is used to illustrate the proposed method. The application of this method can make the quality analysis of parts 3D model more effective, accurate, and efficient. This paper can not only help enterprises identify higher-weight and error-prone design factors, but also guide designers in modeling.

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