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Robot Vision SS 2005 Matthias Rüther 1 ROBOT VISION Lesson 5: Camera Hardware and Technology Matthias Rüther.

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Presentation on theme: "Robot Vision SS 2005 Matthias Rüther 1 ROBOT VISION Lesson 5: Camera Hardware and Technology Matthias Rüther."— Presentation transcript:

1 Robot Vision SS 2005 Matthias Rüther 1 ROBOT VISION Lesson 5: Camera Hardware and Technology Matthias Rüther

2 Robot Vision SS 2005 Matthias Rüther 2 Content  Camera Hardware –Sensors –Video Data Transfer –Mechanics  Optics –Lenses –Macroscopic –Telecentric –Microscopic  Illumination –Illumination systems –Mechanical Arrays

3 Robot Vision SS 2005 Matthias Rüther 3 Sensors  Goal: convert light intensity to electrical signal –Mostly visible light spectrum (~700nm to ~400nm) provides color information, light intensity, like human eye –Near infrared (~700nm to 5  m) Similar properties as visible light, NO heat information; black sky, plants are white, used for vegetation inspection, remote sensing, to detect reflective markers

4 Robot Vision SS 2005 Matthias Rüther 4 Sensors –Ultraviolet (~400nm to ~240nm) Used with special illumination, UV microscopy (resolution up to 100nm) surface inspection (detecting cracks, fluid leaks etc.) flame inspection (alcohol flames are barely visible to human eye) Forensics (finger print, blood, etc.)

5 Robot Vision SS 2005 Matthias Rüther 5 Sensors  2 Basic Technologies –Charge Coupled Device –CMOS Sensor  Both are pixelated metal oxide semiconducters  Accumulate in each pixel signal charge proportional to local illumination intensity => spatial sampling function  Properties –Responsivity: amount of output signal per unit of input optical energy –Dynamic range: ratio of saturation level to signal threshold –Uniformity: consistency of response –Shuttering: start and stop of exposure –Speed: frame rate / readout time –Windowing: can subwindows of the chip be sampled? –Antiblooming –Biasing / Clocking –Reliability –Cost

6 Robot Vision SS 2005 Matthias Rüther 6 Charge Coupled Device

7 Robot Vision SS 2005 Matthias Rüther 7 CMOS Sensor

8 Robot Vision SS 2005 Matthias Rüther 8 CCD vs CMOS

9 Robot Vision SS 2005 Matthias Rüther 9 Line Sensor

10 Robot Vision SS 2005 Matthias Rüther 10 Line Sensor

11 Robot Vision SS 2005 Matthias Rüther 11 Video Data Transfer  Transfer of image data from Camera to System Memory  Properties: –Transfer distance –Bandwidth / Framerate –Analog / Digital –Environment –Cost

12 Robot Vision SS 2005 Matthias Rüther 12 Analog Video Signal  Video Standards –Composite Video: de facto standard for consumer products, combines color, brightness and synchronisation data to one „composite“ signal. –S-Video: Y/C or Component Video; splits video data in two channels: luminance (Y) and chrominance (C). Provides less granularity and sharper image. C = U/V for PAL and C = I/Q for NTSC –RGB: standard for computer monitors. Four signals (red, green, blue, sync) –Large distances possible (~20m). Higher frequencies degrade with length (low pass) and noise adds to the signal.

13 Robot Vision SS 2005 Matthias Rüther 13 Analog Video Signal  Broadcast Standards (combine technical and legal definitions) –NTSC: National Television Standards Comitee; North/Central America, Mexico, Canada, Japan. –PAL: Phase Alteration Line; UK, Western Europe, Middle East, Parts of Africa and South America –SECAM: Systeme Electronic Pour Coleur Avec Memoire, similar to PAL, chrominance is FM modulated; France, Russia, parts of Africa, Eastern Europe FormatCountryMode Signal Name Frame Rate [fps] Vert. Line Resolution Line Rate [lps] Img. Size NTSCUS, JapanMonoRS x480 ColorNTSC Color PALEurope except France MonoCCIR x576 ColorPAL Color SECAMFrance, East. Europe Mono N/A Color

14 Robot Vision SS 2005 Matthias Rüther 14 Analog Video Signal  Scanning Process

15 Robot Vision SS 2005 Matthias Rüther 15 CameraLink  Serial Interface for digital image transfer.  Standardized  Fast (up to 2.38 Gbps)  Not a High Volume Product -> expensive  Max 10m cable, no power provided  Physical Layer: Low Voltage Differential Signaling (LVDS); high- speed, low-power general purpose interface standard; known as ANSI/TIA/EIA-644, approved in March –350 mV nominal signal swing –Theoretical Gbps  Connection Channellink: developed by Natioan Semiconducturs for flat panel displays, –28bit I/O, serialized 7:1 and transferred –Up to 2.38 Gbps  Cameralink specializes Channellink for video data transfer.

16 Robot Vision SS 2005 Matthias Rüther 16 CameraLink

17 Robot Vision SS 2005 Matthias Rüther 17 IEEE 1394 (Firewire)  De-facto industrial standard –Moderate volume product (Industrial cameras, Video Cameras, Webcams) –Consists of both hardware and software specification –Completely digital--no conversion to analog –Data rates of 100, 200, or 400 Mb per second (800Mbps by 1394b) –Flexible--supports daisy-chain and branching cable configurations –Inexpensive –Max 4.5m cable length –Power provided by bus –Invented by Apple in mid 90‘s as LAN bus (100Mbps) –Development hampered by license fees in 1998 ($1 per port) –Since 1999 owned by 1394LA ($0.25 per unit) –Firewire remains trademark of apple.

18 Robot Vision SS 2005 Matthias Rüther 18 USB 2.0  Upcoming rival for IEEE1394 –Fast (480Mbps) –High volume (available on every PC) –Plug and Play –Emerged from USB 1.1 (1995) –Provides Power –5m cable length –Master-Slave Architecture (IEEE1394: Peer to Peer) –IEEE1394 is faster (10-70%), due to protocol architecture!

19 Robot Vision SS 2005 Matthias Rüther 19 Mechanics  Industrial cameras need to be ruggedized –Up to 90% humidity –-5 to +50 degrees Celsius –Harder requirements for outdoor/surveillance cameras  Common Sensor dimensions: –¼“ –1/3“ –½“ –2/3“ –1“  Mounting usually by ¼“ screws  Lens mount standards: C-mount and CS-mount; 1“ thread; differing by flange focal distance

20 Robot Vision SS 2005 Matthias Rüther 20 Optics … or how to calculate the focal length.  Lenses (or lens systems, a „compound“ lens) are used to project light rays on an image sensor.  If all rays originating from a distinct point of light intersect in one point on the image plane, a sharp image of this point is acquired.

21 Robot Vision SS 2005 Matthias Rüther 21 Lens Parameters  Magnification = size of image / size of object –E.g. size of object = 5cm; size of image = 5mm -> magnification = 0.1 –Depends on working distance (lens – object distance) -> impractical for standard lenses  Focal length = working distance * size of image / (size of object + size of image) –E.g. to capture a 1000m wide object from 500m on a CCD chip measuring 4.8x6.4mm, you need 3.2mm of focal length

22 Robot Vision SS 2005 Matthias Rüther 22 Lens Iris  The Iris limits the amount of light getting through the lens.  -> the image appears darker (avoids overexposure in bright scenes)  -> less lens area is used -> fewer lens errors are incorporated  -> sharpness is increased  Sharpness: theoretically impossible to focus 3D object, but: –Blurred points of some size appear sharp to human eye (e.g. on 35mm film, 1/30mm spots appear sharp) –-> „Depth of field“ –In practice: max. blurred spot is 1 pixel

23 Robot Vision SS 2005 Matthias Rüther 23 Lens Iris  Depth of field limits: –Wd = working distance –Bs = size of blur spot –I = amount of iris aperture –F = focal length e.g.: a 10mm wide object is imaged on a 1/3“ Megapixel CCD from a distance of 100mm, the blurred spot size is max. 5μm -> best f is 26.5mm, choose 25mm standard lens -> DOF=  0.08mm at full aperture -> DOF=  0.24mm at aperture = 4

24 Robot Vision SS 2005 Matthias Rüther 24 Lens types  Standard lenses: focal length from 5mm to 75mm –Adjustable/fixed focus –Adjustable/fixed Iris –Adjustable/fixed zoom (focal length)  Macro lenses –Near field imaging (wd ~75mm-90mm, dof ±0.06mm… ±5mm, magnification 0.14…8)  Telecentric lenses –Parallel projection, moving object towards lens does not change the image

25 Robot Vision SS 2005 Matthias Rüther 25 Lighting  Illumination is the most critical part in a machine vision system.  Small illumination changes may severely affect performance of vision algorithms.  If possible, adjust lighting conditions and keep them fixed!  Properties: –Intensity –Spectrum –Frequency (amplitude change: flicker, strobe) –Direction  Hazards: –Object: reflection, specularity, color, stray light, transparency, motion –Lamp: heat, flicker, stability, lifetime, size, power, speed

26 Robot Vision SS 2005 Matthias Rüther 26 Regulated Halogen Lamp Systems  Illumination by Quartz-Halogen lamps  High power output  Power control by Voltage regulation and adjustable shutter  Fiber optic light guidance to avoid heating  High power consumption (150W lamp)  Heavy DC power source necessary to avoid flicker  Lamp life: hrs

27 Robot Vision SS 2005 Matthias Rüther 27 Light Emitting Diodes  Possible to generate all primary colors  Bright White LED‘s possible (up to 5W per piece) -> Cooling  Life time: hrs  Low power consumption -> Small DC current source  Small/light housing  Fast strobe (time limited by driver circuit, down to 1μs pulses)  Packed in LED arrays

28 Robot Vision SS 2005 Matthias Rüther 28 Types of Illumination  Directional  Glancing  Diffuse

29 Robot Vision SS 2005 Matthias Rüther 29 Types of Illumination  Ring Light  Diffuse Axial  Brightfield/Backlight

30 Robot Vision SS 2005 Matthias Rüther 30 Types of Illumination  Darkfield  Structured Light (Line Generators)


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