What Is Machine Vision?

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What Is Machine Vision?

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:Automated inspection of manufactured products for

quality and process control

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Human vs. Machine Vision

Human Vision– Recognition– Hand-eye

coordination– Inspection– Find Position– Gather Information– Safety– ----------

Machine Vision– Identification– Robot Guidance– Inspection– Find position– ----------– ----------– ----------– Measure

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Human vs. Machine Vision

• Human Vision– High image resolution– Interprets complex scene quickly– Operates in visible light spectrum– Adapts to variables

• Machine Vision– Consistent, tireless– May operate in visible, infra-red, x-ray, etc.– Operates in hostile environments– Follows program precisely

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Why Use Machine Vision?

• High speed production lines• Microscopic inspection• Clean room environments• Hazardous environments• Closed-loop process control• Robot guidance• Precise non-contact measurement

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Image Processing vs. Image AnalysisImage Processing: Image Enhancement

• meteorology: weather mapping• medical: x-rays, CAT scans, MRI• military: spy satellites, target tracking• NASA: space exploration

Image Analysis: Machine Vision• part location• gauging and measurement• character recognition• quality inspection

Image Processing Image Analysis

image imageimage• decision• answer• location

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Machine Vision Applications

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What can Machine Vision Do?

• Robot guidance– Determine part position (x, y, and angle) for robotic

arm pick and place operations

• Identification and sorting– Determine the identities of objects and sort

accordingly

• 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

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What Can Machine Vision Do?

• Presence / Absence Checking, Assembly Verification– Verify that part components are present and in the

correct locations

• Dimensional Gauging– Calculate the distance between two or more points on

an object

• Defect detection– Identify defects and calculate defect characteristics

such as position and size

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What Can Machine Vision Do?

• Optical Character Recognition (OCR), Optical Character Verification (OCV)– Read (determine the character identities

without prior knowledge) or verify (confirm the presence of a given character sequence) a string of characters

• Bar Code Reading, 2-D Inspection– Decode bar codes and 2-D matrices

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Where Is Machine Vision Used?

Medical/Pharmaceutical

Electronics/Computer Industry

Consumer Products

Graphic Arts/ Packaging

Automotive Industry

Semiconductor Industry

Food Packaging IndustryShipping/TransportationShipping/Transportation

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Case #1: Presence/Absence Detection

Problem:– Ketchup bottles are not all filled properly.

Manual Solution:– Manually inspect every ketchup bottle coming down the line

Problem with Manual Solution:– Operators become bored and tired and miss some half-full bottles– Operators cannot keep up with the speed of the production line

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Vision Principle #1:

One way to tell if something is missing is to look for a change in grey value (how dark or light something is)

Fill Line Look in this region foran average grey valueindicating ketchup ispresent.

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Case #2: Assembly VerificationProblem:

– Buttons on phones are not inserted in the correct places

Manual Solution:– Sample inspection of phones at the end of the production line (1

out of every 50 phones are checked) – Some incorrectly assembled touch pads are not caught– Customers return defective phones and complain

1 2 3

4 5 6

7 8 9

* 0 #

1 2 3

4

5 6

7 8 9

* 0

#Bad Good

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Vision Principle #2:

To determine if something is positioned correctly, train a model of the feature, set a search region, and search for it.

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4 5 6

7 8 9

* 0 #

Search regionfor first model

1First model

Models are taughtand search regionsare defined for all12 numbers and symbols.

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Case #3: Gauging

Problem:– Spark plugs are gapped incorrectly

Manual Solution:– Customers must adjust the plug gap manually or risk problems,

such as an engine that runs poorly

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Vision Principle #3:To measure the distance between two edges, first locate 2

points along one edge and create a line. Next, locate a point on the other edge. Finally, measure the distance between the point and the line perpendicular to the line to find the shortest distance.

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Case #4: Part Location (Fixturing)

Problem:– Fuses come down the production line in semi-random location

and orientation. In order to take precise measurements, the fuses must be located and fixtured.

Manual Solution:– Operators manually pick fuses off the production line and place

them in fixtures for spot inspections. Hundreds of fuses still go unchecked.

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Vision Principle #4:To fixture a part that varies in location and orientation,

locate the part using PatMax, a searching tool that tolerates rotation and scale changes. Then, create a part coordinate system based on PatMax results and locate all measurements according to that part coordinate system.

X

Y

Part Coordinate System

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Case #5: Defect DetectionProblem:

– Detect defects on watch faces

Manual Solution:– Operators manually inspect 1 in 10 watches on the assembly

line, resulting in false accepts and missed inspections.

Watch without Defects Watch with Defects

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6

9

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Vision Principle #5:• Save in the vision system an image of a good part, often called the

“Golden Template”• Compare the production image with the golden template by using

PatInspect

• Whatever is different between the two images will show up in the Difference Image

Golden Template Image

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Image with Defects

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Difference Image

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Case #6: Optical Character RecognitionProblem:

– Read microscopic serial numbers inscribed onto a chip mounted on disk drive slider heads

Manual Solution– Serial numbers read by human and manually entered into a

database, frequently resulting in mismatched data, wasted material, & expensive rework further down the production line

SN128664A

serial number on chip

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Vision Principle #6:• Use one of the fonts provided by Cognex, which

contains a representation of each character. The OCR tool selects the font characters which best match the serial number characters, and reports the result.

Font Character Models

A B DC EGF 0 1 243 5 6 798 0 Report the best match

Result: 128664A

Compare

Serial Number

1 2 68 6 4 A

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Creating a Vision System

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Vision System Components

CameraDisplay

Parts

Light Source

Vision Sensor

Output / Communications:• Discrete I/O• Serial • EthernetInput/Communications:

• Discrete I/O• Serial • Ethernet

Lens

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A Typical Vision System at Work

3. Strobe is flashed to illuminate part

2. Proximity or other sensor detects part and sends a trigger to the vision sensor

1. Part arrives at inspection station

4. The image is acquired and digitized within the vision sensor.

5. Vision software running in vision sensorperforms image processing and/or image analysison acquired image

6. Vision sensor sends signal along a discrete output line which activates a diverter if the part does not meet acceptance criteria.

7. Operator can view rejected parts and ongoing statistics on display,and can take system off-line if necessary

FAIL!

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