150819 Intro to Machine Vision Slides

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Introduction to Machine Vision

Samantha Frost

Product Marketing Manager, Vision


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2 | 2015 Cognex Corporation

Agenda

What is machine vision?Why use machine vision?

Machine vision applications

Types of machine vision systemsVision system components

Machine vision terms

Improving vision system performance

Summary

Q&A


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What is machine vision?


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A simple concept

Formal definition:

Machine vision is the use of devices for optical non-

contact sensing to automatically receive and interpret an

image of a real scene in order to obtain information

and/or control machines or processes.- from the Society of Manufacturing Engineers

or more simply:Capturing an image from an industrial camera for

inspection or process control of manufactured products.


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Evolution of machine vision

Proprietary Box Embedded

Boards

Modular

Vision

Barcode

Readers

PC Vision

Vision

Sensors

1982 Today

3D Displacement

Sensors


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Simple examples

Machine vision systems analyze images Then makes decisions and/or returns numeric results

about each image it gets

6

The center tab on this bracket is

37.255 mm wide

Good Oil

Filter all

holes are

open

Reject oil

filter some

holes are

blocked


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Image analysis

The primary purpose of machine vision is imageanalysis

Image

Decision

Answer

Location



Poll question #1

What is your level of machine vision experience?a. Im completely new to machine vision and have

never used it before

b. Im a beginner with limited machine vision

experience

c. Im an intermediate user, familiar with different

types of machine vision technology

d. Im an advanced user, but theres always more tolearn



Where is machine vision used?

Automotive Industry

Graphic Arts/ Packaging

Consumer Products

SemiconductorIndustry

Shipping/Transportation

Electronics/Computer

Industry

Medical/Pharmaceutical

Food Packaging

Industry


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Why use machine vision?



A critical role in achieving strategic goals

High speed production lines

Clean room environments

Hazardous environments

Microscopic inspection

Closed-loop process control

Robot guidance

Precise non-contact measurement



Benefits of machine vision

Strategic Goal Machine Vision Applications

Higher Quality Inspection, measurement, gauging, andassembly verification

Increased Productivity Repetitive tasks formerly done manually are

now done by MVS

Production Flexibility Measurement and gauging / Robot guidance /

Prior operation verificationLess Machine Downtime and

Reduced Setup Time

Changeovers programmed in advance

More Complete Information

and Tighter Process Control

Manual tasks can now provide computer data

feedback



Benefits of machine vision

Strategic Goal Machine Vision Applications

Lower Capital EquipmentCosts Adding vision to a machine improves itsperformance, avoids obsolescence

Lower Production Costs One vision system vs. many people / Detection

of flaws early in the process

Scrap Rate Reduction Inspection, measurement, and gauging

Inventory Control OCR and Identification

Reduced Floorspace Vision System vs. Operator


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Poll question #2

What is your principal objective for attending this

webinar?

a. I am looking for a basic introduction to machine

vision

b. I want to know what kind of problems machinevision can solve

c. I want to know the basic components of a vision

system and understand how they work togetherd. I want to know which basic vision concepts I need

to master


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Machine vision applications


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Think: GIGI

Guidance Inspection Gauging Identification


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Guidance

Determines part position (x, y, and angle)

Automates handling of parts for machines:

Alignment & Placement

2D & 3D Picking

Eliminates need for fixturing & improves robot

flexibility Vision tool alignment, fixturing

Locate at least one feature on a part for the

purpose of calculating the (x, y) position and

rotation of the part to position other vision tools

precisely

*First step in every vision application is to

find the part or features of interest
http://localhost/var/www/apps/conversion/tmp/scratch_7/Delta%20Robot%20-%20PackExpo%2003.mpg


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Trained Part

Out of focus

180 Rotation

Reversed Polarity Occlusion

Scale ChangeDim Lighting

Confusing Background

Geometric pattern matching


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Part location challenges

Appearance changes


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Part location challenges

Presentation / Distortion effects

2


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Inspection

Broad category of vision applications:

Correct location Orientation

Skew

Quality

Defect Detection Surface Inspection

Contaminants

Completeness Fill Level

Feature Presence

Counting

Assembly Verification


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Gauging

Precise dimensioning

Automated metrology and data recording

Ensure tolerances

Diameters, Gaps, Bushings, Threads, etc.


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Identification

Read codes

Bar codes & 2-D Matrix

Labels & direct part mark

Read characters OCR / OCV

Recognize objects

Based on color, shape, or size


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Types of machine vision systems


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1-D machine vision

100% continuous web

inspection and classificationUses line-scan cameras

Materials inspected include:

Metals

Non-wovens

Plastics

Paper


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2-D machine visionArea scan

480

768

1200

640 1024 1600


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2-D machine visionLine scan

Built Image

Line Acquired

In-Sight

5604

Line Light

Conveyor

Belt

Movement

Encoder Shaft

Image is built line by line

Movement is neededRequires encoder to track movement

Short exposure times


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Four reasons to use Line scan

1. Unwrap cylindrical objects for

inspection

2. Add vision to space-constrained

environments

3. Meet high-resolution inspection

requirements

4. Inspect objects in continuous

motion


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3-D machine vision


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Machine vision system components

f h


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Key parts of a machine vision system

POWER

A-BALLEN-BRADLEY

INPUT

1

0

2

3

4

56

7

SLC5/04CPU

RUN

FLTBAT

FORC

DH+RS232

RUN REMPROG

INPUT

1

0

2

3

4

56

7

OUTPUT

1

0

2

3

4

56

7

Display

Inputs/Outputs: switches, PLCs, robots, lights

Light Source

Vision System

Vision Software

I/O

Comm.

CameraLens

i i ll h
http://www.sensource.biz/PDF/BR-Photoelectric.pdf


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Putting it all together

Camera

Monitor

Operator Pointing Device

(Trackball, Mouse, Touchscreen)

Parts

Light Source

Vision System

Output:

SerialParallel

ISA, PCI, VME bus

Input:

Serial

Parallel

ISA, PCI, VME bus

Lens

H h k


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How the system works

3. Strobe is flashed to

illuminate part

2. Sensor detects part and sends a trigger to the vision system

1. Part arrives at inspection

station

4. Vision System acquires the image from the sensor.

5. Software algorithms running on vision system

performs image processing and/or image analysis

on acquired image

6. Vision system sends signal along a discrete output line

which activates a diverter if the part is bad

7. Operator can view rejected parts and ongoing statistics on display,

and can take system off-line if necessary

FAIL!

M hi i i l i h


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Machine vision algorithms

Transforms raw numbers into

useful higher level features Raw numbers turned into edges, colors,

characters, and other characteristics

then makes decisions Returns answers such as position, similarity,

distance, presence, quality

All within just tens to hundreds of milliseconds!

P ll ti #3


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Poll question #3

What would you say are the principal challenges to

implementing successful machine vision on yourassembly/production line?

a. The management of my organization does not realize thevalue of machine vision

b. Our line moves really fast and we have not found a vision

system that can keep up with itc. We have variable lighting and/or environmental conditions

that make it difficult to capture a consistent image

d. The conditions of the attributes we need to analyze (e.g.,codes, markings, etc.) are often so degraded that wecannot read them

e. None of the above


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Machine vision terms

Vi i d fi iti


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Vision definitions

Field of View (FOV)

The part which can be

seen by the machine

vision system at one

moment. The field of view

depends from the lens ofthe system and from the

working distance between

object and camera.

5 x 7

Fi ld f i


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Field of view

What is my field of view?3

4

8

15

W ki di t d l ti


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Working distance and resolution

Working Distance (WD)

Distance between the FRONTof

the lens and the target

Resolution

The minimum feature size ofthe object under inspection.

10

Workin Distan e and FOV are Interrelated


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Working Distance and FOV are Interrelated

Depth of field


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Depth of field

Depth of Field (DOF)

The distance in front of

and behind the object

which appears to be in

focus

3

More DOF with a small aperture

(high f/number) than with a

large aperture (low f/number)


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Improving vision system performance

Different lens same image?


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Different lens same image?

Lighting

Depth of field

Working distance

Line speed

Exposure time

Aperture

Budget

Lighting techniques


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Lighting techniques

4

Bright Field

Dark FieldBack Lighting

Diffuse Dome

Axial Diffuse

Light can be structured in different ways. Angle and direction of the light

determine how the mark and space is seen by the camera.

Structured

To learn more about choosing the

right lighting go to Cognex.com >Resources > White Papers and

Articles

Optics


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Optics

To learn more about choosing theright optics go to Cognex.com >

Resources > On-Demand Webinars

Filtering techniques


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Filtering techniques

Control quality and quantity

of light

Block all unwanted

ambient lighting

Pass only the output of

lighting used for inspection

Increase contrast

and resolution

For more on optical filters, go toCognex.com > Resources > On-

Demand Webinars

Image pre processing tools


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Image pre-processing tools

To learn more about image pre-processing, goto Cognex.com > Resources > On-Demand

Webinars

Summary


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Summary

Make products better, faster, and less expensivelyGauging, Inspection, Guidance, and Identification are

the key applications

Key components are the lens, camera, lighting, visionsoftware and communications

Learn more about optics, lighting, filters and image pre-

processing to improve system performance

Dont go it aloneget help from experts!


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Thank you for your time

150819 Intro to Machine Vision Slides

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