An introduction to real time machine vision in mechatronics
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An Introduction to Real-time Machine Vision in Mechatronics. Dr. Onur TOKER. Outline. RT Machine Vision ? Mechatronics ? Review of previous experiments Image sensors (CMOS versus CCD) CMUCam, and cwCAM Interfacing a CCD camera to an 8-bit uC Difficulties in real-time machine vision

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An introduction to real time machine vision in mechatronics

An Introduction to Real-time Machine Vision in Mechatronics

Dr. Onur TOKER


  • RT Machine Vision ? Mechatronics ?

  • Review of previous experiments

  • Image sensors (CMOS versus CCD)

  • CMUCam, and cwCAM

  • Interfacing a CCD camera to an 8-bit uC

  • Difficulties in real-time machine vision

  • Conclusion

Dr. Onur TOKER

Rt machine vision mechatronics
RT Machine Vision ? Mechatronics ?

  • Machine vision is the ability of a computation machine to "see."

  • Visual object tracking

  • Object recognition

  • Automated inspection, sorting

  • Pattern recognition, etc.

RT: There is no strict real-time system. There are systems with very short event response latency times.

Dr. Onur TOKER

Experiment 1
Experiment #1

  • 1-D tracking system

  • Analog video camera & PCI grabber

  • VB 6 & VFW based

  • Simple algorithm

  • PID control

  • Pentium 2/350MHz

Dr. Onur TOKER

Experiment 2
Experiment #2

  • Line following

  • Wireless video camera and ToyCar

  • Processing on a remote PC

  • VC++ & DirectX based

  • Simple algorithm

  • Pentium 3/1GHz

Dr. Onur TOKER

Experiment 3
Experiment #3

  • Intel 8051

  • Very primitive machine vision

  • Rapid prototyping board

  • LDR sensor

  • MOSFET driver

Dr. Onur TOKER

Experiment 31
Experiment #3

Dr. Onur TOKER

Prototyping final product
Prototyping / Final product

Final design EPROM based minimum size PCB

Prototyping board Serial download, EEPROM based, 9V battery

Dr. Onur TOKER

A student project
A Student Project

Line following robot

Phototransistor based sensors

Dr. Onur TOKER

Boe bot kit

Simple kit


Not very flexible

Very small RAM


photo transistors

Dr. Onur TOKER

Boe bot demo
BOE-BOT demo

Dr. Onur TOKER

Other demos
Other demos

CMUCam demo

(Color tracking)

WAM demo (MIT 1995)

(Tracking by stereo machine vision)

Dr. Onur TOKER

Image sensor types
Image sensor types

  • Charged coupled devices (CCD)

  • Charge injection devices (CID)

  • CMOS Active Pixel Sensors (CMOS)

  • They all convert incident light (photons) into electronic charge (electrons) by a photo-conversion process.

  • Color sensors can be made by coating each individual pixel with a filter color (e.g. red, green, and blue).

  • Beyond that point, everything is different.

Dr. Onur TOKER

Cmos image sensors
CMOS image sensors

Digital output

Easy to interface

A CMOS sensor (OV7620)

CUMCam uses such a sensor 2nd PCB has a Scenix uC


Dr. Onur TOKER

Ccd image sensors
CCD image sensors

Analog output

Difficult to interface

Require several support chips


Dr. Onur TOKER

Cmos versus ccd
CMOS versus CCD

Under same lightning,

same distance,

comparable budget,

CCD image is better.

CMOS sensor

640x480 mode

CCD sensor

640x480 (NTSC output)

Dr. Onur TOKER

Cmucam architecture
CMUCam architecture




CMOS sensor


Serial I/O

  • “User device” issues high level commands

  • SX28 does the processing (Limited built-in functions)

  • SX28 replies

Dr. Onur TOKER

What is wrong with cmucam
What is wrong with CMUCam ?

  • Serial I/O (Low bandwidth)

  • Low frame rate (Max. 17fps)

  • CMOS sensor

  • Processing done by SX28

  • Limited to built in functions

  • Not much flexibility

  • Instead of FPGA, uses SX28

  • Very compact design

Dr. Onur TOKER

Proposed cwcam architecture
Proposed cwCam architecture



CCD camera



Video ADC


  • Co-operating windowing approach (Discussed later)

  • Parallel processors

  • Parallel application specific digital architectures in the FPGA

  • ASIC CPU cores in FPGA

Dr. Onur TOKER

Machine vision with an analog industrial camera
Machine Vision with an Analog Industrial camera

  • NTSC/30fps or PAL/25fps

  • Even/odd field interlacing: 60fips/50fips rate

  • 31ms VSYNC, 4.7us HSYNC for NTSC

  • Needs a high speed ADC (AD9048 is 35 MHz)

  • Most 8-bit uCs are too slow for this task

  • Scenix SX28AC/DP 13.3 ns instruction cycle

  • FPGA for accurate and high resolution capture

Dr. Onur TOKER

Digitized video signal
Digitized video signal

One field

One frame


Dr. Onur TOKER

A single field
A single field


Several HSYNCs

Dr. Onur TOKER

Video adc speed
Video ADC speed ?



Conclusion:Use 10MHz ADC

Dr. Onur TOKER

Scenix sx28ac dp
Scenix SX28AC/DP

  • 13.3 ns instruction cycle (75MHz clock)

  • 10MHz video sampling = 100 ns loop time

  • 1 Branch=3 cycles

  • 4 instruction loop OK, but int. RAM too small

  • 8051 too slow !

  • PIC16F877 too slow !


Dr. Onur TOKER

Our fpgas prototyping boards
Our FPGAs (Prototyping boards)

Spartan II FPGA 50 Kgate



Dr. Onur TOKER

Our adc ad9048
Our ADC (AD9048)

Actual photo of AD9048 used in our video digitizer

  • 35MSPS, 8-bit Flash ADC, Bipolar, 550mW, DIP 28 available

  • AD9203, 40MSPS, 10-bit,CMOS, 74mW, No DIP available

Dr. Onur TOKER

Cortex i approach
Cortex-I approach

  • Bederson, 1992

  • Logarithmic structured space variant pixel geometry

  • Based on human vision system

  • For real-time machine vision, reduce data to < 1500 pixels

Dr. Onur TOKER

Co operating windowing 1
Co-operating windowing (1)

  • Nassif & Capson, 1997

  • 2 Watch windows (200x20)

  • 1 Peripheral window (40x40 … 200x200)

  • 1 Foveal window (20x20)

  • Object tracking at 113Hz

Dr. Onur TOKER

Where we are at cwcam
Where we are at cwCAM ?

  • AD9048 Video ADC board design completed (PCB layout !)

  • AD9048 interfaced to 8051 prototyping board and tested

  • Logic design is being done by Xilinx ISE software

  • Mixed VHDL and graphical logic designs

  • Tedious and long task


CCD camera


Video ADC

Dr. Onur TOKER

Human vision
Human Vision ?

PUMA robot arm and dual camera set

HMD and Dual monitor support

Dr. Onur TOKER


  • Real time machine vision requires innovative use of software and hardware techniques.

  • Cortex-I (Human Eye), Co-operating windowing, etc.

  • Innovative use of FPGAs and uC/DSPs.

  • High frame rate CCD sensors.

  • Optimum designs likely to be an application specific one.

  • cwCAM is based on co-operating windowing approach and innovative hardware/software techniques.

Dr. Onur TOKER

An introduction to real time machine vision in mechatronics


Dr. Onur TOKER