Defect inspection and extraction of the mobile phone cover glass based on the principal components analysis

Li, Di; Liu, Liang; Zhang, Wu-jie

doi:10.1007/s00170-014-5871-y

Cited by 62 publications

(17 citation statements)

References 11 publications

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“…The image (5) is the corresponding reconstructed binary image of image (4). The image (6) reveals that the profi le fl aws in the mirror appearance are exactly identifi ed in a binary image, no matter of thecurved surfaces and high refl ection. Selection of the key parameter Pr, retaining rate, in the FDs method will signifi cantly infl uence the inspection results of the damaged edges.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…Numerous research examined the visual fl aw detection of glass-related goods. Li et al [6] applied the principal components analysis approach to inspect surface defects on the mobile phone cover glass. Lin and Tsai [7] presented a Fourier transform-based method to inspect linear fl aws on surfaces of capacitive touch displays.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Since the edge point number of testing objects are distinct in applications of industrial inspection, we select a fi xed percentage of the total number of edge points as the recovery points. The fi xed percentage is called retaining rate Pr and the number of recovery points is determined as: (6) In general, the Pr values within 5% ~ 10% can rebuild an approximated shape of a boundary [23]. If an object with a large indentation needs to be recovered, a less retaining rate will be selected.…”

Section: Image Modelingand Analysismentioning

confidence: 99%

See 2 more Smart Citations

Effective image models for inspecting profile flaws of car mirrors with applications

Peter¹,

Lin²,

Lin³

2020

J Appl Eng Science

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Since car mirrors are standard accessories with cars, the demand for car mirrors is growing and manufacturers also pay more emphasis on the increase of product quality. Common appearance fl aws of car mirrors include: scratches, bubbles, pinholes causing surface fl aw type and burrs,damaged edges causing profi le fl aw type. Currently, the inspection tasks are conducted by human inspectors. Since the profi le fl aws will cause structural damages of car mirrors and reduce ability to withstand stress, the level of damage suffered even more than the surface fl aws. In addition, the angle diversity of capturing images makes it hard to implement automatic optical inspection. Therefore, this study develops an automated profi le fl aw detection system for car mirrors to replace visual inspection personnel. This study proposes a self-contrast defect detection method for the profi le fl aw inspection of car mirrors. It is not required to provide a standard fl awless sample in detection process and derive information compared with testing samples. The proposed method fi rst extracts the contour information of the testing image by Fourier descriptors. Then, after some middle and high-frequency coeffi cients were fi ltered out, an approximated contour image can be rebuilt from the Fourier domain for comparing with the testing image. Finally, the fl aw districts are easily separated by image subtraction. Experimental results demonstrate that the fl aw inspection rate reaches 85.05%, and the incorrect alert rate is smaller than 0.07%, and the correct classifi cation rate is up to 97.47%.

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Section: Experiments and Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Image Modelingand Analysismentioning

confidence: 99%

See 1 more Smart Citation

Effective image models for inspecting profile flaws of car mirrors with applications

Peter¹,

Lin²,

Lin³

2020

J Appl Eng Science

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“…Today, AVI systems have been developed with various systems that automatically check the surface quality of various kinds of products [4]. Among these systems, the first thing to be considered may be a lack of consistency in data due to differences in sensors or cameras, etc.…”

Section: Detecting Defect Proceduresmentioning

confidence: 99%

76‐5: Late‐News Paper: Enhanced Productivity Performance through Detecting Defects on Surface of AMOLED Display

Park

Cho

Heo

et al. 2019

Symp Digest of Tech Papers

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At this time, the system with advanced automatic detection capability has consistent execution results and has been verified that it can be used as a necessary tool for cost reduction and the quality control of the product, which is the value of the customer. It will contribute to reducing human error and minimizing defects by designing a system that relies on more mechanization automation, taking into account the characteristics of the machine as well as the role of humans and machines.

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“…this paper is a new method of analysis and processing data that the blade crown samples of the turbine blade were inspected to obtain the images using ultrasonic phased array instrument, and the accurate defects were finally recognized by filtering, edge detection and morphological operation etc. [12]- [15]. Then, quantitative and qualitative analysis and the location of the defects were discussed.…”

Section: Introductionmentioning

confidence: 99%

The Detection for Nickel Base Super Alloy Based on Ultrasonic Phased Array

Gao¹,

Li²,

Chen³

et al. 2017

IJMMM

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Abstract-The material of the gas turbine blade is nickel base super alloy. When the blades are inspected the artificial evaluation can only be adopted to normal inspection due to the lack of industry benchmarks, which contributes to single indicator and large error. To solve this troublesome problem and help inspect the blades, this paper proposes a method of data analysis and processing. At first, the defects were recognized from the detected image, and then quantitation, qualification and location analysis were made from the recognized defects. Through comparing with the artificial evaluation, this method is a good one which can provide more parameters, has high accuracy and much reliability.Index Terms-Gas turbine, image processing, defect analysis, nickel base super alloy.

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Defect inspection and extraction of the mobile phone cover glass based on the principal components analysis

Cited by 62 publications

References 11 publications

Effective image models for inspecting profile flaws of car mirrors with applications

Effective image models for inspecting profile flaws of car mirrors with applications

76‐5: Late‐News Paper: Enhanced Productivity Performance through Detecting Defects on Surface of AMOLED Display

The Detection for Nickel Base Super Alloy Based on Ultrasonic Phased Array

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