Parametric Study of Diffusion-Enhancement Networks for Spatiotemporal Grouping in Real-Time Artificial Vision

Computer vision systems are an essential part in industrial automation tasks such as: identification, selection, measurement, defect detection and quality control in parts and components. There are smart cameras used to perform tasks, however, their high acquisition and maintenance cost is restrictive. In this work, a novel low-cost artificial vision system is proposed for classifying objects in real time, using the Raspberry Pi 3B + embedded system, a Web camera and the Open CV artificial vision library. The suggested technique comprises the training of a supervised classification system of the Haar Cascade type, with image banks of the object to be recognized, subsequently generating a predictive model which is put to the test with real-time detection, as well as the calculation for the prediction error. This seeks to build a powerful vision system, affordable and also developed using free software.

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A Homogeneous Algorithm for Motion Estimation and Compensation by Using Cellular Neural Networks

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2010.5.2231 ◽

2010 ◽

Vol 5 (5) ◽

pp. 719 ◽

Cited By ~ 1

Author(s):

Cristian Grava ◽

Alexandru Gacsádi ◽

Ioan Buciu

Keyword(s):

Neural Networks ◽

Motion Estimation ◽

Real Time ◽

Cellular Neural Networks ◽

Image Sequences ◽

Artificial Vision ◽

Real Time Image ◽

Field Programmable ◽

Real Time Applications ◽

Time Image

In this paper we present an original implementation of a homogeneous algorithm for motion estimation and compensation in image sequences, by using Cellular Neural Networks (CNN). The CNN has been proven their efficiency in real-time image processing, because they can be implemented on a CNN chip or they can be emulated on Field Programmable Gate Array (FPGA). The motion information is obtained by using a CNN implementation of the well-known Horn & Schunck method. This information is further used in a CNN implementation of a motion-compensation method. Through our algorithm we obtain a homogeneous implementation for real-time applications in artificial vision or medical imaging. The algorithm is illustrated on some classical sequences and the results confirm the validity of our algorithm.

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Embedded Implementation of a Resource-Efficient Optical Flow Extraction Method

MACRo 2015 ◽

10.1515/macro-2015-0016 ◽

2015 ◽

Vol 1 (1) ◽

pp. 163-175

Author(s):

László Bakó ◽

Sándor-Tihamér Brassai ◽

Călin Enăchescu

Keyword(s):

Mobile Robot ◽

Optical Flow ◽

Real Time ◽

Extraction Method ◽

Artificial Vision ◽

Time Motion ◽

Motion Extraction ◽

Egomotion Estimation ◽

Vision Based Navigation ◽

Embedded Implementation

AbstractThe main goal of the proposed project is to enhance a mobile robot with evolutionary optimization capabilities for tasks like egomotion estimation and/or obstacle avoidance. The robot will learn to navigate different environments and will adapt to changing conditions. This implies the implementation of vision-based navigation of robots using artificial vision, computed with on-board FPGAs. The current paper aim to contribute on the implementation of a real-time motion extraction from video a feed using embedded FPGA circuits.

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A Real-Time NDGPS/INS Navigation System Based on Artificial Vision for Helicopter

IFAC Proceedings Volumes ◽

10.3182/20080706-5-kr-1001.02203 ◽

2008 ◽

Vol 41 (2) ◽

pp. 13028-13033

Author(s):

Jae Hyung Kim ◽

Joon Lyou

Keyword(s):

Real Time ◽

Navigation System ◽

Artificial Vision

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Microcomputer-based artificial vision support system for real-time image processing for camera-driven visual prostheses

Journal of Biomedical Optics ◽

10.1117/1.3292012 ◽

2010 ◽

Vol 15 (1) ◽

pp. 016013 ◽

Cited By ~ 7

Author(s):

Cindy X. You

Keyword(s):

Image Processing ◽

Real Time ◽

Support System ◽

Artificial Vision ◽

Real Time Image Processing ◽

Real Time Image ◽

Time Image

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Feasibility of Contact Elimination of a Mechanical Face Seal Through Clearance Adjustment

Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar Award; General ◽

10.1115/99-gt-147 ◽

1999 ◽

Cited By ~ 1

Author(s):

Min Zou ◽

Joshua Dayan ◽

Itzhak Green

Keyword(s):

Pattern Recognition ◽

Power Spectrum ◽

Real Time ◽

Parametric Study ◽

Experimental Results ◽

Face Seal ◽

Angular Misalignment ◽

Adjustment Mechanism ◽

Mechanical Face Seal

The feasibility of eliminating contact in a noncontacting flexibly mounted rotor (FMR) mechanical face seal is studied. The approach for contact elimination is based on a parametric study using FMR seal dynamics. Through clearance adjustment it is possible to reduce the maximum normalized relative misalignment between seal faces and, therefore, eliminate seal face contact Clearance is measured by proximity probes and varied through a pneumatic adjustment mechanism. Contact is determined phenomenologically from pattern recognition of probe signals and their power spectrum densities as well as angular misalignment orbit plots, all calculated and displayed in real-time. The contact elimination strategy is experimentally investigated for various values of stator misalignment and initial rotor misalignment Contrary to intuition but compliant with the parametric study, the experimental results show that for the seal under consideration contact can be eliminated through clearance reduction.

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