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 Conclusion Dr. Onur TOKER

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 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 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 Intel 8051 Very primitive machine vision Rapid prototyping board LDR sensor MOSFET driver Dr. Onur TOKER

Experiment #3 Dr. Onur TOKER

Prototyping / Final product Final design EPROM based minimum size PCB Prototyping board Serial download, EEPROM based, 9V battery Dr. Onur TOKER

Phototransistor based sensors A Student Project Line following robot Phototransistor based sensors Dr. Onur TOKER

BOE-BOT kit Simple kit PBASIC Not very flexible Very small RAM IR LEDs & photo transistors Dr. Onur TOKER

BOE-BOT demo Dr. Onur TOKER

(Tracking by stereo machine vision) Other demos CMUCam demo (Color tracking) WAM demo (MIT 1995) (Tracking by stereo machine vision) Dr. Onur TOKER

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

CUMCam uses such a sensor 2nd PCB has a Scenix uC CMOS image sensors Digital output Easy to interface A CMOS sensor (OV7620) CUMCam uses such a sensor 2nd PCB has a Scenix uC DALSA CMOS Sensor Dr. Onur TOKER

CCD image sensors Analog output Difficult to interface Require several support chips DALSA CCD Sensor Dr. Onur TOKER

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 SX28 CMOS sensor uC uC/DSP 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 ? 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 uC/DSP CCD camera FPGA uC/DSP Video ADC uC/DSP 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 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 One field One frame VSYNC Dr. Onur TOKER

A single field VSYNC Several HSYNCs Dr. Onur TOKER

Conclusion:Use 10MHz ADC Video ADC speed ? HSYNC ??? VSYNC Conclusion:Use 10MHz ADC Dr. Onur TOKER

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 ! USE AN FPGA ! Dr. Onur TOKER

Our FPGAs (Prototyping boards) Spartan II FPGA 50 Kgate 8MB RAM 8051 Dr. Onur TOKER

Actual photo of AD9048 used in our video digitizer 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 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) Nassif & Capson, 1997 2 Watch windows (200x20) 1 Peripheral window (40x40 … 200x200) 1 Foveal window (20x20) Object tracking at 113Hz Dr. Onur TOKER

Co-operating windowing (2) Dr. Onur TOKER

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 cwCam CCD camera FPGA Video ADC Dr. Onur TOKER

PUMA robot arm and dual camera set Human Vision ? PUMA robot arm and dual camera set HMD and Dual monitor support Dr. Onur TOKER

Conclusion 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

QUESTIONS ? Dr. Onur TOKER