scholarly journals Research of Image processing in Instant Noodle Packets Auto-Inspection System

2012 ◽  
Author(s):  
Kai Peng ◽  
Tie-Cheng Wang ◽  
Ze-Qing Yang
Keyword(s):  
Image Processing ◽  
Inspection System ◽  
Instant Noodle

scholarly journals A Study on Pre-processing Algorithms for Metal Parts Inspection

2011 ◽  
Vol 7 (1) ◽  
pp. 1-4
Author(s):  
Haider Hashim ◽  
Anton Prabuwono ◽  
Siti Norul Huda Abdullah
Keyword(s):  
Image Processing ◽  
Morphological Analysis ◽  
Image Understanding ◽  
Detection Methods ◽  
Experimental Result ◽  
Inspection System ◽  
Metal Parts ◽  
Analysis Task ◽  
Processing Step ◽  
Filter Noise

Pre-processing is very useful in a variety of situations since it helps to suppress information that is not related to the exact image processing or analysis task. Mathematical morphology is used for analysis, understanding and image processing. It is an influential method in the geometric morphological analysis and image understanding. It has befallen a new theory in the digital image processing domain. Edges detection and noise reduction are a crucial and very important pre-processing step. The classical edge detection methods and filtering are less accurate in detecting complex edge and filtering various types of noise. This paper proposed some useful mathematic morphological techniques to detect edge and to filter noise in metal parts image. The experimental result showed that the proposed algorithm helps to increase accuracy of metal parts inspection system.

scholarly journals Smart Dye Inspection System in Textile Industry

2020 ◽  
Vol 8 (6) ◽  
pp. 5061-5063
Keyword(s):  
Image Processing ◽  
Reference Material ◽  
Textile Industry ◽  
High Accuracy ◽  
Inspection System ◽  
Manual Operation ◽  
Image Processing Techniques ◽  
Manual Inspection ◽  
Processing Techniques

Inspection on the dyed material in the textile industry is facing a challenging task owing to the accurate measurement of the dye concentration added. Currently manual inspection is done. It consumes more time and less accurate. The proposed work provides a solution to above problem. The image of reference material (cloth) is captured and the features are extracted using image processing techniques. The color concentration of both the reference material and the test fabric is compared. If the dye concentration of the test fabric matches with the reference material, then it is a perfect dyed cloth whereas for mismatched samples, the concentration is to be adjusted is displayed. This smart dyeing inspection system reduces the manual operation and saves time and results in high accuracy.

Development of Cable Inspection System Based on Image Processing

2014 ◽  
Vol 602-605 ◽  
pp. 2199-2204
Author(s):  
Huan Liu ◽  
Chao Tao Liu
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Image Segmentation ◽  
Image Enhancement ◽  
Image Recognition ◽  
Host Computer ◽  
Inspection System ◽  
Energy Distributions ◽  
Single Motor ◽  
Image Acquisition System

A stayed cable inspection system was developed which consists of robot, host computer, cameras and image acquisition system. The robot was driven with single motor and could climb cables of various and variable diameters. Pictures of the cables’ were taken by the robot, and the defects and mars were identified automatically with image recognition. The steps of image recognition includes image de-noising, image enhancement, image segmentation, feature extraction, and recognition with the features of the images’ histogram grayscale distributions and energy distributions.

Rapid and non-invasive surface crack detection for pressed-panel products based on online image processing

2019 ◽  
Vol 18 (5-6) ◽  
pp. 1928-1942 ◽  
Author(s):  
Hwee Kwon Jung ◽  
Gyuhae Park
Keyword(s):  
Image Processing ◽  
Manufacturing Process ◽  
Crack Detection ◽  
Experimental Results ◽  
Inspection System ◽  
Camera System ◽  
Non Invasive ◽  
Panel Products ◽  
Traditional Approaches ◽  
Detection And Localization

Crack detection during the manufacturing process of pressed-panel products is an important aspect of quality management. Traditional approaches for crack detection of those products are subjective and expensive because they are usually performed by experienced human inspectors. Therefore, the development and implementation of an automated and accurate inspection system is required for the manufacturing process. In this article, a crack detection technique based on image processing is proposed that utilizes the images of panel products captured by a regular camera system. First, the binary panel object image is extracted from various backgrounds after considering the color factor. Edge lines are then generated from a binary image using a percolation process. Finally, crack detection and localization is performed with a unique edge-line evaluation. In order to demonstrate the capability of the proposed technique, lab-scale experiments were carried out with a thin aluminum plate. In addition, a test was performed with the panel images acquired at an actual press line. Experimental results show that the proposed technique could effectively detect panel cracks at an improved rate and speed. The experimental results also demonstrate that the proposed technique could be an extension of structural health monitoring frameworks into a new manufacturing application.

Development of an ultrasonic weld inspection system based on image processing and neural networks

2017 ◽  
Vol 33 (2) ◽  
pp. 229-236 ◽  
Author(s):  
Fernando Roca Barceló ◽  
Pedro Jaén del Hierro ◽  
Fran Ribes Llario ◽  
Julia Real Herráiz
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Inspection System ◽  
Weld Inspection
Sign in / Sign up

Export Citation Format

Share Document