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Robot Vision SS 2012 Matthias Rüther 1 ROBOT VISION Camera Hardware and Technology Matthias Rüther
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Robot Vision SS 2012 Matthias Rüther 2 Content Camera Hardware –Sensors –Video Data Transfer –Mechanics Optics –Lenses –Macroscopic –Telecentric –Microscopic Illumination –Illumination systems –Mechanical Arrays
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Robot Vision SS 2012 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
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Robot Vision SS 2012 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.)
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Robot Vision SS 2012 Matthias Rüther 5 Sensors 2 Basic Technologies: Charge Coupled Device (CCD) CMOS Sensor (CMOS) Both are pixelated metal oxide semiconducters Accumulate in each pixel signal charge proportional to local illumination intensity => spatial sampling function
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Robot Vision SS 2012 Matthias Rüther 6 Photon Sensing
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Robot Vision SS 2012 Matthias Rüther 7 Charge Transport
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Robot Vision SS 2012 Matthias Rüther 8 Read Out
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Robot Vision SS 2012 Matthias Rüther 9 Full-Frame CCD
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Robot Vision SS 2012 Matthias Rüther 10 Frame Transfer CCD
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Robot Vision SS 2012 Matthias Rüther 11 Interline Transfer CCD
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Robot Vision SS 2012 Matthias Rüther 12 CMOS: Passive Pixel Sensor (PPS)
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Robot Vision SS 2012 Matthias Rüther 13 CMOS: PPS with Column Amplifiers
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Robot Vision SS 2012 Matthias Rüther 14 CMOS: Active Pixel Sensor (APS)
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Robot Vision SS 2012 Matthias Rüther 15 CMOS: APS Variations On-Chip A/D Column A/D
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Robot Vision SS 2012 Matthias Rüther 16 CMOS: APS Variations Pixel A/D
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Robot Vision SS 2012 Matthias Rüther 17 CMOS Pixels Passive Pixel –1T, 2 lines –high fill factor, high noise Photodiode APS –3T, 4 lines –low fill factor, medium noise
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Robot Vision SS 2012 Matthias Rüther 18 CMOS Pixels Pinned Photodiode APS –4T, 5lines –Low fill, low noise, low full well –Correlated Double Sampling (CDS) Pinned Photodiode (5T) –5T, 5lines –Low fill, low noise, low column FPN, low full well
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Robot Vision SS 2012 Matthias Rüther 19 CMOS vs CCD
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Robot Vision SS 2012 Matthias Rüther 20 APS Pixel
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Robot Vision SS 2012 Matthias Rüther 21 CCD vs CMOS
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Robot Vision SS 2012 Matthias Rüther 22 CCD vs CMOS
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Robot Vision SS 2012 Matthias Rüther 23 CCD vs CMOS
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Robot Vision SS 2012 Matthias Rüther 24
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Robot Vision SS 2012 Matthias Rüther 25 CMOS / CCD
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Robot Vision SS 2012 Matthias Rüther 26 CMOS Rolling Shutter
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Robot Vision SS 2012 Matthias Rüther 27 Line Sensor
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Robot Vision SS 2012 Matthias Rüther 28 Line Sensor
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Robot Vision SS 2012 Matthias Rüther 29 Video Data Transfer Transfer of image data from Camera to System Memory Properties: –Transfer distance –Bandwidth / Framerate –Analog / Digital –Environment –Cost Popular Digital Transfer Protocols: –USB 2.0 (480 Mbps) –IEEE1394 a/b (400 / 800 Mbps) –Gigabit Ethernet (1 / 10 Gbps) –Cameralink (2 / 4 / 5.5 Gbps)
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Robot Vision SS 2012 Matthias Rüther 30 CameraLink Serial Interface for digital image transfer. Standardized!!!!! Fast (up to 2.04 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 1996. –350 mV nominal signal swing Connection Channellink: developed by National Semiconducturs for flat panel displays, –28bit I/O, serialized 7:1 and transferred –Up to 2.04 Gbps Cameralink specializes Channellink for video data transfer.
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Robot Vision SS 2012 Matthias Rüther 31 CameraLink Mode A: 2.04 Gbps, 1 ChannelLink (blue) Mode B: 4.08 Gbps, 2 ChannelLink (blue). Requires 2 Connectors Mode C: 5.44 Gbps, 3 ChannelLink (blue). Requires 2 Connectors
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Robot Vision SS 2012 Matthias Rüther 32 IEEE 1394 (Firewire) De-facto industrial standard, being replaced by GigE –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 –1394b may run over GOF (Glass Optical Fiber), hundreds of meters of 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.
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Robot Vision SS 2012 Matthias Rüther 33 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) –IEEE1394a is faster (10-70%), due to protocol architecture!
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Robot Vision SS 2012 Matthias Rüther 34 GigE Gigabit Ethernet –Fast (1 Gbps full duplex, 10 Gbps available soon) –Max Cable length: 100m –Carrier: copper, fiber optics, microwave –High volume (available on every PC) –Plug and Play –May be integrated in standard LANs –No power over cable (except PoE devices). –High power consumption of devices –No Quality of Service –No Isochronous transfer –Packet overhead
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Robot Vision SS 2012 Matthias Rüther 35 Future 10 Gigabit Ethernet –Most Proven –Might become future standard USB 3.0 –Bad in Cable length (unspecified) –No Optical medium –Super Speed 5Gbps Thunderbolt (Lightpeak) –10 Gbps –Industry waits for cable specs –Next generation from Intel planned (optical 50Gbps)
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Robot Vision SS 2012 Matthias Rüther 36 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
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Robot Vision SS 2012 Matthias Rüther 37 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.
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Robot Vision SS 2012 Matthias Rüther 38 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 / size of image = working distance / size of object 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
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Robot Vision SS 2012 Matthias Rüther 39 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
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Robot Vision SS 2012 Matthias Rüther 40 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
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Robot Vision SS 2012 Matthias Rüther 41 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
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Robot Vision SS 2012 Matthias Rüther 42 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
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Robot Vision SS 2012 Matthias Rüther 43 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: 200-10000hrs
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Robot Vision SS 2012 Matthias Rüther 44 Light Emitting Diodes Possible to generate all primary colors Bright White LED‘s possible (up to 5W per piece) -> Cooling Life time: 100000+ 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
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Robot Vision SS 2012 Matthias Rüther 45 Types of Illumination Directional Glancing Diffuse
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Robot Vision SS 2012 Matthias Rüther 46 Types of Illumination Ring Light Diffuse Axial Brightfield/Backlight
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Robot Vision SS 2012 Matthias Rüther 47 Types of Illumination Darkfield Structured Light (Line Generators)
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