What Is Machine Vision? PreviousNext X. What Is Machine Vision? Formal definition: Machine vision is the use of devices for optical non- contact sensing.

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Presentation transcript:

What Is Machine Vision? PreviousNext X

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 PreviousNext X

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 PreviousNext X

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 PreviousNext X

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 PreviousNext X

Image Processing vs. Image Analysis Image 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 decision answer location PreviousNext X

Machine Vision Applications PreviousNext X

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 PreviousNext X

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 PreviousNext X

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 PreviousNext X

Where Is Machine Vision Used? Medical/Pharmaceutical Electronics/Computer Industry Consumer Products Graphic Arts/ Packaging Automotive Industry Semiconductor Industry Food Packaging Industry Shipping/Transportation PreviousNext X

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 PreviousNext X

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 for an average grey value indicating ketchup is present. PreviousNext X

Case #2: Assembly Verification Problem: –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 * 0# * 0 # Bad Good PreviousNext X

Vision Principle #2: To determine if something is positioned correctly, train a model of the feature, set a search region, and search for it * 0 # Search region for first model 1 First model Models are taught and search regions are defined for all 12 numbers and symbols. PreviousNext X

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 PreviousNext X

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. PreviousNext X

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. PreviousNext X

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 PreviousNext X

Case #5: Defect Detection Problem: –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 PreviousNext X

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 Image with Defects Difference Image PreviousNext X

Case #6: Optical Character Recognition Problem: –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 PreviousNext X

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 ABDCE GF Report the best match Result: A Compare Serial Number A PreviousNext X

Creating a Vision System PreviousNext X

Vision System Components Camera Display Parts Light Source Vision Sensor Output / Communications: Discrete I/O Serial Ethernet Input/Communications: Discrete I/O Serial Ethernet Lens PreviousNext X

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 sensor performs image processing and/or image analysis on 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! PreviousNext X