A machine vision extension for the Ruby programming language

Dynamically typed scripting languages have become popular in recent years. Although interpreted languages allow for substantial reduction of software development time, they are often rejected due to performance concerns. In this paper we present an extension for the programming language Ruby, called HornetsEye, which facilitates the development of real-time machine vision algorithms within Ruby. Apart from providing integration of crucial libraries for input and output, HornetsEye provides fast native implementations (compiled code) for a generic set of array operators. Different array operators were compared with equivalent implementations in C++. Not only was it possible to achieve comparable real-time performance, but also to exceed the efficiency of the C++ implementation in several cases. Implementations of several algorithms were given to demonstrate how the array operators can be used to create concise implementations.</p

Tracking translucent objects in cluttered scenes

This paper discusses the issues involved in tracking translucent objects in a cluttered environment. It also discusses steps taken to address those issues and the design of a successful method to track the object. The designed method is an adaptation of the particle filtering method which predicts the probable locations of the object. The method has been successfully tested on a real image sequence that contains a translucent glass pipett

Development of a desktop freehand 3-D surface reconstruction system

This paper discusses the development of a freehand 3-D surface reconstruction system. The system was constructed by making use of readily available off-the-shelf components, namely a laser line emitter and a webcam. The 3-D laser scanner system allows the user to hand sweep the laser line across the object to be scanned. The 3-D surface information of the object Is captured as follows. A series of digital images of the laser line, generated by the intersection of the laser plane, the surface of the object and the background planar object were captured and stored in a PC. The points on the laser line were extracted. The 2-D laser points that were found on the surface of the planar object were projected onto the 3-D space using a pinhole camera model. The laser plane was calibrated. Using the 2-D laser points found on the surface of the 3-D object, a cloud of 3-D points which represent the surface of the object being scanned was generated by triangulation. For the laser plane calibration two different methods were implemented. Their performance were compared

Machine vision methods for autonomous micro-robotic systems

Purpose - To develop customised machine vision methods for closed-loop micro-robotic control systems. The micro-robots have applications in areas that require micro-manipulation and micro-assembly in the micron and sub-micron range. Design/methodology/approach - Several novel techniques have been developed to perform calibration, object recognition and object tracking in real-time under a customised high-magnification camera system. These new methods combine statistical, neural and morphological approaches. Findings - An in-depth view of the machine vision sub-system that was designed for the European MiCRoN project (project no. IST-2001-33567) is provided. The issue of cooperation arises when several robots with a variety of on-board tools are placed in the working environment. By combining multiple vision methods, the information obtained can be used effectively to guide the robots in achieving the pre-planned tasks. Research limitations/implications - Some of these techniques were developed for micro-vision but could be extended to macro-vision. The techniques developed here are robust to noise and occlusion so they can be applied to a variety of macro-vision areas suffering from similar limitations. Practical implications - The work here will expand the use of micro-robots as tools to manipulate and assemble objects and devices in the micron range. It is foreseen that, as the requirement for micro-manufacturing increases, techniques like those developed in this paper will play an important role for industrial automation. Originality/value - This paper extends the use of machine vision methods into the micron range

Computer vision methods for optical microscopes

As the fields of micro- and nano-technology mature, there will be an increased need to build tools that are able to work in these areas. Industry will require solutions for assembling and manipulating components, much as it has done in the macro range. With this need in mind, a new set of challenges requiring novel solutions have to be met. One of them is the ability to provide closed-loop feedback control for manipulators. We foresee that machine vision will play a leading role in this area. This paper introduces a technique for integrating machine vision into the field of micro-technology including two methods, one for tracking and one for depth reconstruction under an optical microscope. (C) 2006 Elsevier B.V. All rights reserved

Combination of principal component analysis and optical-flow motion compensation for improved cardiac MR thermometry

International audienc

Improved Cardiac Magnetic Resonance-Thermometry and dosimetry for monitoring lesion formation during catheter ablation

International audienc

Developing robust vision modules for microsystems applications

In this work, several robust vision modules are developed and implemented for fully automated micromanipulation. These are autofocusing, object and end-effector detection, real-time tracking and optical system calibration modules. An image based visual servoing architecture and a path planning algorithm are also proposed based on the developed vision modules. Experimental results are provided to asses the performance of the proposed visual servoing approach in positioning and trajectory tracking tasks. Proposed path planning algorithm in conjunction with visual servoing imply successful micromanipulation tasks