Automatic Inspection Method of Steady Arm Slope Based on Computer Vision

2010 ◽  
Author(s):  
Rujiao Duan ◽  
Wei Zhao ◽  
Songling Huang ◽  
Jianye Chen
Keyword(s):  
Computer Vision ◽  
Automatic Inspection ◽  
Inspection Method

A New Method for Railway Fastener Detection Using the Symmetrical Image and Its EA-HOG Feature

2019 ◽  
Vol 34 (02) ◽  
pp. 2055006
Author(s):  
Jiajia Liu ◽  
Jianying Yuan ◽  
Yongfang Jia
Keyword(s):  
Computer Vision ◽  
Sparse Representation ◽  
Efficient Method ◽  
Important Task ◽  
New Method ◽  
Automatic Inspection ◽  
Test Image ◽  
Recognition Result ◽  
The Status ◽  
Railway Operation

Railway fastener recognition and detection is an important task for railway operation safety. However, the current automatic inspection methods based on computer vision can effectively detect the intact or completely missing fasteners, but they have weaker ability to recognize the partially worn ones. In our method, we exploit the EA-HOG feature fastener image, generate two symmetrical images of original test image and turn the detection of the original test image into the detection of two symmetrical images, then integrate the two recognition results of symmetrical image to reach exact recognition of original test image. The potential advantages of the proposed method are as follows: First, we propose a simple yet efficient method to extract the fastener edge, as well as the EA-HOG feature of the fastener image. Second, the symmetry images indeed reflect some possible appearance of the fastener image which are not shown in the original images, these changes are helpful for us to judge the status of the symmetry samples based on the improved sparse representation algorithm and then obtain an exact judgment of the original test image by combining the two corresponding judgments of its symmetry images. The experiment results show that the proposed approach achieves a rather high recognition result and meets the demand of railway fastener detection.

Computer Vision Based Technique for Surface Defect Detection of Apples

2014 ◽  
pp. 111-121
Author(s):  
C. J. Prabhakar ◽  
S. H. Mohana
Keyword(s):  
Computer Vision ◽  
Defect Detection ◽  
Surface Defects ◽  
Quality Standards ◽  
Production Costs ◽  
Automatic Inspection ◽  
Segmentation Technique ◽  
Surface Defect Detection ◽  
Fruit Grading

The automatic inspection of quality in fruits is becoming of paramount importance in order to decrease production costs and increase quality standards. Computer vision techniques are used in fruit industry for fruit grading, sorting, and defect detection. In this chapter, we review recent approaches for automatic inspection of quality in fruits using computer vision techniques. Particularly, we focus on the review of advances in computer vision techniques for automatic inspection of quality of apples based on surface defects. Finally, we present our approach to estimate the defects on the surface of an apple using grow-cut and multi-threshold based segmentation technique. The experimental results show that our method effectively estimates the defects on the surface of apples significantly more effectively than color based segmentation technique.

scholarly journals Computer vision–based automatic rod-insulator defect detection in high-speed railway catenary system

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877394 ◽  
Author(s):  
Ye Han ◽  
Zhigang Liu ◽  
DJ Lee ◽  
Wenqiang Liu ◽  
Junwen Chen ◽  
...  
Keyword(s):  
Computer Vision ◽  
Defect Detection ◽  
High Speed ◽  
Power Transmission ◽  
Estimation Algorithm ◽  
Inspection System ◽  
High Speed Railway ◽  
Inspection Method ◽  
Railway Systems ◽  
Catenary System

Maintenance of catenary system is a crucial task for the safe operation of high-speed railway systems. Catenary system malfunction could interrupt railway service and threaten public safety. This article presents a computer vision algorithm that is developed to automatically detect the defective rod-insulators in a catenary system to ensure reliable power transmission. Two key challenges in building such a robust inspection system are addressed in this work, the detection of the insulators in the catenary image and the detection of possible defects. A two-step insulator detection method is implemented to detect insulators with different inclination angles in the image. The sub-images containing cantilevers and rods are first extracted from the catenary image. Then, the insulators are detected in the sub-image using deformable part models. A local intensity period estimation algorithm is designed specifically for insulator defect detection. Experimental results show that the proposed method is able to automatically and reliably detect insulator defects including the breakage of the ceramic discs and the foreign objects clamped between two ceramic discs. The performance of this visual inspection method meets the strict requirements for catenary system maintenance.

INSPECTION AND QUALITY CHECKING OF CERAMIC CUP USING MACHINE VISION TECHNIQUE: DESIGN AND ANALYSIS

2017 ◽  
Vol 79 (5-2) ◽  
Author(s):  
Nursabillilah Mohd Ali ◽  
Mohd Safirin Karis ◽  
Siti Azura Ahmad Tarusan ◽  
Gao-Jie Wong ◽  
Mohd Shahrieel Mohd Aras ◽  
...  
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Machine Vision ◽  
Image Sensor ◽  
Histogram Method ◽  
Inspection Method ◽  
Inspection Process ◽  
Set Up ◽  
Vision Application ◽  
Vision Technique

The development of inspection and quality checking using machine vision technique are discussed where the design of the algorithm mainly to detect the sign of defect when a sample product is used for inspection purposes. There are several constraints that a machine need to be improved based on technology used in vision application. CMOS image sensor as well as programming language and open source computer vision library were used in designing the inspection method. Experimental set-up was conducted to test the proposed technique for evaluate the effectiveness process. The experimental results were obtained and represented in graphical and image processing form. Besides, analysis and discussion were made according to obtained results. The proposed technique is able to perform the inspection process using good and defect ceramic cup based on detection technique. Moreover, based on the analysis gathered, the proposed technique able to differentiate between good and defect ceramic cup. The result shows that there is a difference frequency by 236 which is 2% of total value in pixels frequency. The frequency indicated as pixel frequency of image using histogram method based on scaled value of image.

scholarly journals SUBPIXEL IMAGE REGISTRATION USING CIRCULAR FIDUCIALS

1994 ◽  
Vol 04 (04) ◽  
pp. 403-422 ◽  
Author(s):  
ALON EFRAT ◽  
CRAIG GOTSMAN
Keyword(s):  
Computer Vision ◽  
Number Theory ◽  
Image Registration ◽  
Practical Importance ◽  
Efficient Algorithms ◽  
Automatic Inspection ◽  
Rotation Invariant ◽  
Registration Accuracy ◽  
Geometric Methods ◽  
Lattice Geometry

The design of fiducials for precise image registration is of major practical importance in computer vision, especially in automatic inspection applications. We analyze the sub-pixel registration accuracy that can, and cannot, be achieved by some rotation-invariant fiducials, and present and analyze efficient algorithms for the registration procedure. We rely on some old and new results from lattice geometry and number theory and efficient computational-geometric methods.

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