ARTIFICIAL VISION FOR THE BLIND: A BIO-INSPIRED ALGORITHM FOR OBJECTS AND OBSTACLES DETECTION

2010 ◽  
Vol 10 (04) ◽  
pp. 531-544 ◽  
Author(s):  
FLORIAN DRAMAS ◽  
SIMON J. THORPE ◽  
CHRISTOPHE JOUFFRAIS
Keyword(s):  
Image Processing ◽  
Sensory Modality ◽  
Three Dimensional ◽  
Processing System ◽  
Visual Image ◽  
Artificial Vision ◽  
Image Processing Algorithm ◽  
Essential Information ◽  
Time Calculation ◽  
Current Systems

Although artificial vision systems could potentially provide very useful input to assistive devices for blind people, such devices are rarely used outside of laboratory experiments. Many current systems attempt to reproduce the visual image via an alternative sensory modality (often auditory or somatosensory), but this dominant "scoreboard" approach, is often difficult to interpret for the user. Here, we propose to offload the recognition problem onto a separate image processing system that then provides the user with just the essential information about the location of objects in the surrounding environment. Specifically, we show that a bio-inspired image processing algorithm (SpikeNet) can not only robustly, precisely, and rapidly recognize and locate key objects in the image, but also in space if the objects are in a stereoscopic field of view. In addition, the bio-inspired algorithm allows real-time calculation of optic flow. We hence propose that this system, coupled with a restitution interface allowing localization in space (i.e. three-dimensional virtual sounds synthesis) can be used to restore essential visuomotor behaviors such as grasping desired objects and navigating (finding directions, avoiding obstacles) in unknown environments.

EMCAT: An automatic image-processing system for electron-microscopic tomography

1994 ◽  
Vol 52 ◽  
pp. 418-419
Author(s):  
Weiping Liu ◽  
John W. Sedat ◽  
David A. Agard
Keyword(s):  
Image Processing ◽  
Structural Information ◽  
Imaging Technique ◽  
Three Dimensional ◽  
Processing System ◽  
Electron Microscopic ◽  
Data Set ◽  
Ordered Structures ◽  
Automatic Image Processing ◽  
Em Tomography

Any real world object is three-dimensional. The principle of tomography, which reconstructs the 3-D structure of an object from its 2-D projections of different view angles has found application in many disciplines. Electron Microscopic (EM) tomography on non-ordered structures (e.g., subcellular structures in biology and non-crystalline structures in material science) has been exercised sporadically in the last twenty years or so. As vital as is the 3-D structural information and with no existing alternative 3-D imaging technique to compete in its high resolution range, the technique to date remains the kingdom of a brave few. Its tedious tasks have been preventing it from being a routine tool. One keyword in promoting its popularity is automation: The data collection has been automated in our lab, which can routinely yield a data set of over 100 projections in the matter of a few hours. Now the image processing part is also automated. Such automations finish the job easier, faster and better.

Mapping of ultrasonic thickness measurements using laser grid projection and image processing

2019 ◽  
Vol 61 (11) ◽  
pp. 643-649 ◽  
Author(s):  
T Tesfaye ◽  
M S Mohammed ◽  
K Ki-Seong
Keyword(s):  
Image Processing ◽  
Three Dimensional ◽  
Pattern Generator ◽  
Mapping Method ◽  
Oxide Semiconductor ◽  
Metal Loss ◽  
Thickness Gauge ◽  
Image Processing Algorithm ◽  
Thickness Measurements ◽  
Ultrasonic Thickness

A three-dimensional surface mapping method for ultrasonic thickness measurements is proposed to enable the dimensions and positions of measured values obtained by the conventional ultrasonic thickness gauges and flaw detectors on curved surfaces to be determined. The proposed system consists of a laser pattern generator and image processing methods. The laser grid produced by the pattern generator is projected onto the surface of the item to be inspected, mathematical relationships are developed to localise the grid nodes on the inspection surface and images are then captured using a complementary metal-oxide semiconductor (CMOS) camera. An image processing algorithm is developed to plot the scanned surface. The measurements performed using a thickness gauge are correlated with the plotted surface, which will enable thickness mapping. The experiments were carried out on a pipe with an artificial metal loss defect and the results showed that the developed method can accurately locate measured thickness values on a three-dimensional plotted surface.

Elastostatic contact imaging for a mechanoreceptive tactile device

Robotica ◽  
1993 ◽  
Vol 11 (4) ◽  
pp. 329-337 ◽  
Author(s):  
M. Mehdian ◽  
P.M. Johns-Rahnejat ◽  
H. Rahnejat
Keyword(s):  
Image Processing ◽  
Three Dimensional ◽  
Processing Algorithm ◽  
Tactile Sensing ◽  
Image Processing Algorithm ◽  
Contact Information ◽  
Three Dimensional Images ◽  
Contact Imaging ◽  
Gripping Force ◽  
Elastostatic Contact

SUMMARYThis paper presents a sensory gripper, consisting of two tactile sensing matrices which acquire three dimensional images of objects of interest. The image processing algorithm uses elastostatic contact information to discriminate among a host of parts made of different materials. The algorithm also enables the assessment of orientation of parts without the pre-requisite of having to recognise them. The positions of stable holdsites and a safe gripping force are also evaluated.

Image intelligent automatic processing analysis based on artificial intelligence vision generator

2020 ◽  
pp. 1-10
Author(s):  
Ruijuan Wang ◽  
Wei Zhuo
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Deep Learning ◽  
Human Error ◽  
Processing System ◽  
Image Data ◽  
Visual Image ◽  
Automated Analysis ◽  
Learning Method ◽  
Deep Learning Model

The image intelligent processing analysis technology uses a computer to imitate and execute some intellectual functions of the human brain, and realizes an image processing system with artificial intelligence, that is, an image processing analysis technology is an understanding of an image. The degree of intelligent automated analysis and processing is low, many operations need to be done manually, causing human error, inaccurate detection, and time-consuming and laborious. Deep learning method can extract features step by step in the original image from the bottom to the top. Therefore, based on feature analysis technology, this paper uses the deep learning method to intelligently and automatically analyse the visual image. This method only needs to send the image into the system, and then the manual analysis is not needed, and the analysis result of the final image can be obtained. The process is completely intelligent and automatically processed. First, improve the deep learning model and use massive image data to choose and optimize parameters. Results indicate that our method not only automatically derives the semantic information of the image, but also accurately understands the image accurately and improve the work efficiency.

Design of a New Image Processing System Based on FPGA

2014 ◽  
Vol 1003 ◽  
pp. 216-220 ◽  
Author(s):  
Qi Li ◽  
Yu Yang ◽  
Zhong Ke Li ◽  
Jing Lu
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Real Time ◽  
Target Detection ◽  
Processing System ◽  
Image Processing Algorithm ◽  
Verilog Hdl ◽  
Video Decoding ◽  
Image Processing System ◽  
Aerial Vehicles

According to the unmanned aerial vehicles real-time video image acquiring and target detection requirements, an image processing system was designed based on FPGA and TVP5150A decoder, and the video decoding hardware and software was also designed to meet the demands of unmanned aerial vehicles. An I2C controller was realized to assure the implementation of video decoding process in accordance with the requirements, and an image processing algorithm and applied to the image recognition process. Both of these were completed in FPGA using verilog HDL language. The correction of this image processing system was verified through real-time experiments.

Experiment Study on Fluidelastic Instability of Tube Bundles Consisting of Different Frequency Tubes With Visual Image Processing System

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Wei Tan ◽  
Zhao Li ◽  
Hao Wu ◽  
Yipeng Wang ◽  
Yanfeng Zhang ◽  
...  
Keyword(s):  
Image Processing ◽  
Processing System ◽  
Visual Image ◽  
Triangular Array ◽  
Image Processing System ◽  
Tube Bundles ◽  
Fluidelastic Instability ◽  
Pitch Ratio ◽  
Assembly Error ◽  
Dispersion Ratio

Fluidelastic instability (FEI) is the most harmful vibration mechanism for heat exchangers. Due to the inevitable manufacturing precision and assembly error, natural frequencies of tubes are not equal in the ideal condition. In order to describe the dispersion characteristic of tube bundles, a new factor named dispersion ratio is proposed in this paper. A series of tubes experiments in normal square and rotated triangular array with pitch ratio s = 1.4 and s = 1.28 were designed and conducted with high-speed camera and visual image processing system. Results show that FEI behaviors of tubes were greatly affected by tubes array geometry, pitch ratio, and dispersion ratio. Reduced critical velocity (Vcr) increased with dispersion ratio in normal square array but no obvious phenomenon was observed in rotated triangular array.

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