Profile Recognition and Mensuration in Machine Vision

1997 ◽  
Vol 119 (3) ◽  
pp. 417-424 ◽  
Author(s):  
S. M. Pandit ◽  
R. Guo
Keyword(s):  
Machine Vision ◽  
Feature Weighting ◽  
Shop Floor ◽  
Sampled Data ◽  
Noisy Environment ◽  
Object Boundary ◽  
Weighting Method ◽  
Characteristic Roots ◽  
Ar Models

This paper presents a systematic profile recognition and mensuration approach in machine vision. It can be utilized to recognize and measure the profiles of industrial parts in an automated manufacturing process by machine vision systems. A new method of profile representation by sampling the data from the object boundary in a digital image is presented. Autoregressive (AR) models are used to code the sampled data of the profiles into AR coefficients for profile recognition. Characterization of the profiles is accomplished by the Data Dependent Systems (DDS) methodology. The AR coefficients and characteristic roots help construct the AR and DDS descriptors to characterize the signatures of the profiles. The frequency domain information about the profiles can be extracted by DDS analysis. The measurement of the profile variation is obtained from the DDS results using optical mensuration method. Neural network and feature weighting method are utilized as reasoning machines for recognition. The illustrative examples in which the profile sampled data are corrupted by noise show that the profile recognition and mensuration approach is very effective and robust in a typical noisy environment on the shop floor.

Machine vision based characterization of particle shape and asphalt coating in Reclaimed Asphalt Pavement

2016 ◽  
Vol 6 ◽  
pp. 26-37 ◽  
Author(s):  
Maziar Moaveni ◽  
Sedat Cetin ◽  
Alexander S. Brand ◽  
Sachindra Dahal ◽  
Jeffery R. Roesler ◽  
...  
Keyword(s):  
Machine Vision ◽  
Particle Shape ◽  
Asphalt Pavement ◽  
Reclaimed Asphalt Pavement ◽  
Reclaimed Asphalt

Mechatronic system for measuring hot-forged automotive parts based on image analysis

2017 ◽  
Vol 40 (13) ◽  
pp. 3774-3787
Author(s):  
Romulo G Lins
Keyword(s):  
Image Analysis ◽  
Statistical Analysis ◽  
Machine Vision ◽  
Experimental Results ◽  
Shop Floor ◽  
Measuring Instruments ◽  
Mechatronic System ◽  
Process Measurement ◽  
Forged Parts ◽  
Automotive Parts

In-process measurement of parts is a field of constant research. Conventionally, industries have used traditional measuring instruments, such as vernier calipers, or even coordinate measuring machines (CMMs), to perform the control quality. In this paper, a system that is both based on machine vision techniques and integrated with a mechatronic system has been developed with the goal of automating the in-process inspection of hot-forged parts. This system uses six cameras, which are installed around the part to be measured. First, the images obtained from the cameras are processed, and thus the part’s dimensions are estimated. Then a statistical analysis is deployed in order to decide if the part may be approved or not. The experimental results validate the application of the proposed method for measuring parts during their processing in real shop floor conditions.

Emotion evolutions of sub-topics about popular events on microblogs

2017 ◽  
Vol 35 (4) ◽  
pp. 770-782 ◽  
Author(s):  
Qingqing Zhou ◽  
Chengzhi Zhang
Keyword(s):  
Design Methodology ◽  
Topic Model ◽  
Feature Weighting ◽  
User Generated Content ◽  
Emotion Classification ◽  
Weighting Method ◽  
Topic Extraction ◽  
Content Type ◽  
Internet Users ◽  
Large Numbers

Purpose The development of social media has led to large numbers of internet users now producing massive amounts of user-generated content (UGC). UGC, which shows users’ opinions about events directly, is valuable for monitoring public opinion. Current researches have focused on analysing topic evolutions in UGC. However, few researches pay attention to emotion evolutions of sub-topics about popular events. Important details about users’ opinions might be missed, as users’ emotions are ignored. This paper aims to extract sub-topics about a popular event from UGC and investigate the emotion evolutions of each sub-topic. Design/methodology/approach This paper first collects UGC about a popular event as experimental data and conducts subjectivity classification on the data to get subjective corpus. Second, the subjective corpus is classified into different emotion categories using supervised emotion classification. Meanwhile, a topic model is used to extract sub-topics about the event from the subjective corpora. Finally, the authors use the results of emotion classification and sub-topic extraction to analyze emotion evolutions over time. Findings Experimental results show that specific primary emotions exist in each sub-topic and undergo evolutions differently. Moreover, the authors find that performance of emotion classifier is optimal with term frequency and relevance frequency as the feature-weighting method. Originality/value To the best of the authors’ knowledge, this is the first research to mine emotion evolutions of sub-topics about an event with UGC. It mines users’ opinions about sub-topics of event, which may offer more details that are useful for analysing users’ emotions in preparation for decision-making.

Large Margin Feature Weighting Method via Linear Programming

2009 ◽  
Vol 21 (10) ◽  
pp. 1475-1488 ◽  
Author(s):  
Bo Chen ◽  
Hongwei Liu ◽  
Jing Chai ◽  
Zheng Bao
Keyword(s):  
Linear Programming ◽  
Feature Weighting ◽  
Weighting Method ◽  
Large Margin

A Machine Vision System for Inspecting Hydraulic Hose Assemblies

1994 ◽  
Author(s):  
Sudhir I. Mehta ◽  
Bruce B. Chenoweth
Keyword(s):  
Quality Control ◽  
Machine Vision ◽  
Human Error ◽  
Vision System ◽  
Control Process ◽  
Shop Floor ◽  
Machine Vision System ◽  
Quality Control Process

Abstract This paper describes a machine vision system for inspecting hydraulic hose assemblies. At present the inspection in this industry is done manually and is prone to human error. A specially designed hose gripping mechanism, a mandrel system, and a camera and lighting fixture allows the system to be integrated on a shop floor and is able to inspect various parameters of a fitting. The system allows the inspection to be done more accurately and improves the quality control process.

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