Hi listers,
The following news release may hold interest for those thinking about the
future development of walking, talking OCR, the ultimate sign readers.
Enjoy,
Bryan Bashin
>Subject: STANFORD NEWS: Speedy camera-on-a-chip unites image capture and
>processing
>
>4/20/01
>
>
>CONTACT: Dawn Levy, News Service (650) 725-1944;
> dawnlevy@stanford.edu
>
>COMMENT: Abbas El Gamal, Electrical Engineering (650) 723-3473;
> abbas@isl.stanford.edu
> Brian Wandell, Psychology (650) 725-2466
> wandell@stanford.edu
>
>EDITORS: A photo of Drs. El Gamal and Wandell with the camera-on-a-chip is
>available on the web at http://newsphotos.stanford.edu. Photo credit: L.A.
>Cicero.
>
>Relevant Web URLs:
>Programmable Digital Camera Project:
>http://www-isl.stanford.edu/~abbas/group/
>
>Speedy camera-on-a-chip unites image capture and processing
>
>Faster than a speeding bullet. Able to leap photographic obstacles with a
>single computer chip. It`s a camera. It`s a chip. It`s a camera-on-a-chip.
>
>Thanks to the efforts of electrical engineering Professor Abbas El Gamal,
>psychology and electrical engineering Professor Brian Wandell and their
>students, it`s getting harder to take a bad picture. Conventional digital
>cameras capture images with sensors and employ multiple chips to process,
>compress and store images. But the Stanford researchers have developed an
>innovative camera that uses a single chip and pixel-level processing to
>accomplish those feats. Their experimental camera-on-a-chip may spawn
>commercial still and video cameras with superpowers including perfect
>lighting in every pixel, blur-free imaging of moving objects, and improved
>stabilization and compression of video.
>
>``The vision is to be able to ultimately combine the sensing, readout,
>digitization, memory and processing all on the same chip,`` says El Gamal.
>``All of a sudden, you`d have a single-chip digital camera which you can
>stick in buttons, watches, cell phones, personal digital assistants and so
>on.``
>
>Most of today`s digital cameras use charge-coupled device (CCD) sensors
>rather than the far less expensive complementary metal-oxide semiconductor
>(CMOS) chips used in most computing technologies. Light arriving at the
>CCD sensor is converted into a pixel charge array. The charge array is
>serially shifted out of the sensor and converted to a digital image using
>an analog-to-digital converter. The digital data are processed and
>compressed for storage and subsequent display.
>
>Reading the data from a CCD is destructive. ``At that point the charge
>within the pixel is gone,`` Wandell says. ``It`s been used in the
>conversion process, and there`s no way to continue making measurements at
>that pixel. If you read the charge at the wrong moment, either too soon or
>too late, the picture will be underexposed or overexposed.``
>
>Another limitation of CCD sensors, El Gamal says, is designers cannot
>integrate the sensor with other devices on the same chip. Creating CMOS
>chips with special circuitry can solve both of these problems.
>
>In 1993, El Gamal began working on image sensors that led to the
>establishment of Stanford`s Programmable Digital Camera Project to develop
>architecture and algorithms capable of capturing and processing images on
>one CMOS chip. In 1998, he, Wandell and James Gibbons, the Reid Weaver
>Dennis Professor of Electrical Engineering, brought a consortium of
>companies together to fund their research effort. Agilent, Canon,
>Hewlett-Packard and Eastman Kodak currently fund the project. Founding
>sponsors included Interval Research and Intel.
>
>Designers of the Mars Polar Lander at NASA`s Jet Propulsion Laboratory
>were the first to combine sensors and circuits on the same chip. They used
>CMOS chips, which could tolerate space radiation better than CCDs, and the
>first-generation camera-on-a-chip was born. It was called the active pixel
>sensor, or APS, and both its input and output were analog.
>
>The Stanford project generated the second-generation camera-on-a-chip,
>which put an analog-to-digital converter in every pixel, right next to the
>photodetector for robust signal conversion. Called the digital pixel
>sensor, or DPS, it processed pixel input serially - one bit at a time.
>
>In 1999, one of El Gamal`s former graduate students, Dave Yang, licensed
>DPS technology from Stanford`s Office of Technology Licensing and founded
>Pixim, a digital imaging company that aims to embed the DPS chip in
>digital still and video cameras, toys, game consoles, mobile phones and more.
>
>The need for speed
>
>The second-generation camera-on-a-chip was relatively peppy at 60 frames
>per second. But the third generation left it in the dust, capturing images
>at 10,000 frames per second and processing one billion pixels per second.
>The Stanford chip breaks the speed limit of everyday video (about 30
>frames per second) and sets a world speed record for continuous imaging.
>
>What makes it so fast? It processes data in parallel, or simultaneously -
>the chip manifestation of the adage ``Many hands make light work.``
>``While you`re processing the first image, you`re capturing the second,``
>El Gamal explains. ``It`s pipelining.``
>
>Besides being speedy, its processors are small. At a Feb. 5 meeting of the
>International Solid State Circuits Conference in San Francisco, El Gamal
>and graduate students Stuart Kleinfelder, Suk Hwan Lim and Xinqiao Liu
>presented their DPS design employing tiny transistors only 0.18 micron in
>size. Transistors on the APS chip are twice as big.
>
>``It`s the first 0.18-micron CMOS image sensor in the world,`` El Gamal
>says. With smaller transistors, chip architects can integrate more
>circuitry on a chip, increasing memory and complexity. This unprecedented
>small transistor size enabled the researchers to integrate digital memory
>into each pixel.
>
>``You are converting an analog memory, which is very slow to read out,
>into a digital memory, which can be read extremely fast,`` El Gamal says.
>``That means that the digital pixel sensor can capture images very quickly.``
>
>The DPS can capture a blur-free image of a propeller moving at 2,200
>revolutions per minute. High-speed input coupled with normal-speed output
>gives chips time to measure, re-measure, analyze and process information.
>Enhanced image analysis opens the door for new or improved research
>applications including motion tracking, pattern recognition, study of
>chemical reactions, interpretation of lighting changes, signal averaging
>and estimation of three-dimensional structures.
>
>Photography is not a new tool in research. In 1872, Leland Stanford hired
>Eadweard Muybridge to conduct photographic experiments testing his idea
>that at one point in its gait, a horse has all four feet off the ground.
>That research led to the development of motion pictures.
>
>But most people don`t use cameras to advance the frontiers of science or
>industry. They just want to take a decent picture, and high-speed capture
>solves a huge problem: getting proper exposure throughout an image with a
>big range of shades between the darkest and brightest portions of the picture.
>
>``It`s very difficult to combine low-light parts of an image with
>high-light parts of an image in one image,`` El Gamal says. ``That`s one
>of the biggest challenges in photography. Film does a very good job of
>that. Digital cameras and video cameras don`t do as well.``
>
>Images taken in bright environments need short film or pixel exposure
>times, and those taken in dim environments need long exposure times. With
>a single click, the camera-on-a-chip captures and measures the charges in
>the pixels repeatedly, at high speed. Its algorithm waits until the right
>moment for each individual pixel to assemble a final picture with perfect
>exposure throughout the image.
>
>``What I consider the real breakthrough of this [DPS] chip is that it can
>do many very fast reads without destroying the data in the sensor,``
>Wandell says.
>
>Wandell, an expert in human vision and color perception, says working with
>cameras gives him ideas for hypotheses about how the brain processes
>images. He and students including Jeffrey DiCarlo and Peter Catrysse in
>electrical engineering and Feng Xiao in psychology have used ideas from
>human vision to create image-processing algorithms to optimize the image
>quality for printing or display on a computer monitor.
>
>While current cameras can focus on objects and judge illumination levels,
>historically they have not been used for image analysis, Wandell says.
>Their forte - image capture - is a ``fundamentally different job,`` he
>says. The human brain`s forte, however, is image analysis, and Wandell
>says future camera designs may borrow from biology to build more
>intelligence into cameras.
>
>-30-
>-By Dawn Levy-
>
>-------------------------------------------------------
>
>News Service website:
>http://www.stanford.edu/news/
>
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>http://news.stanford.edu/
>
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>
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>Phone: (650) 723-2558
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