SeePLANE I-Cube Presented by Barry T. Fryer Dudley (MBA {IT}; MSc {Image Analysis}

Frame Work of Presentation Introduction to IA / LPR (Theory) SeePlane Value proposition (3 options)

Over 1,000 OCR Systems in 30 Countries USA Mexico Colombia Brazil Portugal Spain UK Holland Italy Hungary Poland Kazakhstan Litha Israel China Hong Kong Korea Taiwan Thailand Singapore Argentina South Africa (over 100 solutions) Australia

SeePlane: System description The system consists of cameras monitoring the weigh bridge lane. All planes passing the cameras will be recorded in terms of the time, lane, direction, plane license number (if present), if allowed to use the lane (white list) and an alarm if the plane is either not allowed to take off or over weight (black list).

SeePlane: System operation The OCR software allows PLANES to be enrolled into a WHITE LIST, which are listed per trip. If an unauthorised OR OVER WEIGHT plane is detected this is recorded. If a plane in the BLACK LIST is detected, an alarm will be generated. If TWO SYSTEMS ARE INSTALLED, the plane average speed will be determined, with an alarm for those above the set average speed.

Neural networks Operating in real time, are being utilised extensively world wide. Here I-CUBE uses NEURAL NETWORKS illustrates the concept to automatically identify a plane. The ability to automatically predict and identify planes which are overweight or speeding saves lives.

A Word About Our Eyes Eyes are very good contrast adjusters, but not good for distinguishing subtle variations in color Eyes can discern about 30 continuous levels of gray or color in a field of view Eyes are not good judges of distance Eyes cannot accurately reproduce measurements Eyes can not work in the dark or 24/7

SAME SIZE???

Why do Image Analysis? Improved Precision /Accuracy in Measurements Reproducibility of Results Higher Throughput than Manual Methods Better Definition of Contrasting Areas More Measurements / Faster Real Time Link to Databases Vehicle: Size Colour Shape Texture Grey level

1 - Capture 2 – Find plane number 3 – OCR 4 – Report OCR - 5 easy steps: 5 – Alarm if overweight or speeding !

Camera/Illumination Units (Up to 6 per system) IP or Frame Grabber PLANE Software + DLL+ Sample Client Program PC Station Included Hardware I/O Card +Terminal Block Power Supply for SCH Point A Point B PLANE SPEEDING SYSTEM

Configuration Possible to have multiple cameras to cover both sides of the planes Database remotely updated: Planes to be expected Automatic Database search (local)

Recognition Rate: 0.2 sec PLANE Size Colour Shape No of trips per day Etc Additional items possibly captured:

Adapting Gigabit Ethernet for Vision Standard packet: 1440 Bytes (56 Bytes header) ”Jumbo” packet: Max Bytes (one 56 Bytes header) 96.1% efficiency* 99,7% efficiency* In combination with a High Performance Driver, based on TCP/IP offload-engine, it provides higher transmission efficiency and drastically reduces CPU usage. (High CPU overhead for sending many small packets) (Very low CPU overhead as only one packet) *) Comparison based on sending bytes of data

Lens Image sensor Digitizing Pre-processing Timing Interface PLC Cat-5e Ethernet cable up to 100 m Local I/Os: -Trigger input -Results output Illumination control Image Processing in PC Illumination (Lens Iris Video) Power Acquire

PC Possible system configurations Point-to-point (One camera, one PC) GigE Switch Many-to-one (Multiple cameras, one PC) One-to-many (broadcast) (One or several cameras, with several PCs)

Control room monitoring Additional value for the airport

OPTIONS? Capital R390, (Install and train on how to use) Rental R9, (5 year period) Cost per R39.04 (based on 250 planes a day)

References B.T. Dudley. "Image Analysis and Waste Technology in Africa", Binary - Computers in Microbiology, 5, 3-4. (1993) B.T. Dudley, A.R. Howgrave-Graham, A.G. Bruton and F.M. Wallis. "The application of digital image analysis to quantifying and measuring UASB digester granules", Biotechnology & Bioengineering. 42, (1993) Castleman, K. R Concepts in Imaging and Microscopy: Color Image Processing for Microscopy. The Biological Bulletin. 194 (2): Russ, J.C The Image Processing Handbook. 2nd ed. CRC Press. Boca Raton, FL. Inoue, S. (1986). Video Microscopy. Plenum Press Internet: Thanks to:

Barry T. DUDLEY (MBA {IT}; MSc {Image Analysis}; BSc {Brewing}; BSc Hons {Waste Technology}) ASD (Average Speed Determination) Cell: +27 (0) MADADENI PH +27 (0) Kloof Falls Rd Fax Kloof, Durban, Kwa-Zulu Natal, 3610, South Africa “..any sufficiently advanced technology is indistinguishable from magic.” Arthur C. Clark Technical QUESTIONS: