3D Imaging Systems for Agricultural Applications

The development of the concepts of precision agriculture and viticulture since the last three decades has shown the need to use first 2D image acquisition techniques and dedicated image processing. More and more needs concern now 3D images and information. The main ideas of this chapter is thus to present some innovations of the 3D tools and methods in the agronomic domain. This chapter will particularly focus on two main subjects such as the 3D characterization of crop using Shape from Focus or Structure from Motion techniques and the 3D use for root phenotyping using rhizotron system. Results presented show that 3D information allows to better characterize crucial crop morphometric parameters using proxy-detection or phenotyping methods.

Machine Vision Application on Science and Industry

Face detection, tracking and recognition is still actual field of human centered technologies used for developing more natural communication between computing artefacts and users. Analyzing modern trends and advances in this field, two approaches for face sensing and recognition have been proposed. The first color/shape-based approach uses sets of fuzzy saturated color regions providing face detection by Fourier descriptors and recognition by SVM. The second approach provides fast face detection by adaptive boosting algorithm, and recognition based on SIFT key point extraction into eye-nose-mouth regions has been improved using Bayesian approach. Designed systems have been tested in order to evaluate capability of the proposed approaches to detect, trace and interpret faces of known individuals registered into facial standard databases providing correct recognition rate in range of 94.5-99.0% with recall up to 46%. The conducted tests ensure that both approaches have satisfactory performance achieving less than 3 seconds for human face detection and recognition in live video streams.

Analysis of New Opotoelectronic Device for Detection of Heavy Metals in Corroded Soils

This study was made to design and an analysis the purpose of novel optoelectronic sensor, with three steps, being the first the use of MatLab software to simulate with a mathematical equation, the operation of the sensor as the electrical conductivity. Other step, was the evaluations with Wein2k using the Density of States (DOS) Theory, as a computational system of the physicochemical, to analyze different materials used, to fabricate the novel sensor, being the material proposed the Gallium Nitride (GaN), in according to the electrical conductivity, and was obtained, to fabricate this type of material with the Chemical Vapor Deposition (CVD) and then was made some evaluations to validate this material. Also was made a microanalysis with the Scanning Electron Microscopy (SEM) to evaluate the metallic surfaces of the electrical connections at micro scale.

Theoretical Methods of Images Processing in Optoelectronic Systems

The chapter covers development of mathematical model of signals in output plane of optoelectronic system with registration of optical signals from objects. Analytical forms for mean values and dispersion of signal and interference components of photo receiver response are given. The mathematical model can be used as a base with detection algorithm development for optical signal from objects. An algorithm of signals' detection in output plane of optoelectronic system for the control is offered. The algorithm is synthesized taking into account corpuscular and statistical properties of optical signals. Analytical expressions for mean values and signal and noise components dispersion are cited. These expressions can be used for estimating efficiency of the offered algorithm by the criterion of detection probabilistic characteristics and criterion of signal/noise relation value. The possibility of signal detection characteristics improvement with low signal-to-noise ratio is shown.

Laser Scanners

The presented book chapter provides an overview and detailed description about actual used laser scanner systems. It explains and compares the mainly used coordinate measurement methods, like Time-of-flight, Phasing and Triangulation and Imaging. A Technical Vision System, developed by the engineering institute at the Autonomous University Baja California (UABC) is presented. The mostly used mechanical principles to position a laser beam in a field of view are described and which mechanical actuators are applied. The reflected laser beam gets measured by light sensors or image sensors, which are explained and some principle measuring circuits are provided. The received measuring data gets post-processed by different algorithm or principles, which close the chapter.

Automated Visual Inspection System for Printed Circuit Boards for Small Series Production

There is a crescent need to produce Printed Circuit Boards (PCB) in a customized and efficient way, therefore, there is an effort from the scientific and industrial community to improve image processing techniques for PCB inspection. The methods proposed at this chapter aim the formation of a system to inspect SMD (Surface Mounted Devices) components in a SSP (Small Series Production), ensuring a satisfactory production quality. This way, a 3-step inspection system is proposed, formed by image preprocessing, feature extraction and evaluation components, based on characteristics related to shape, positioning and histogram of the component. The inspection machine used in this project is inserted in a cooperation among machines context, in order to provide a fully autonomous factory, coordinated by a multi-agent system. Experimental obtained results show that the proposed inspection system is suitable for the case, reaching a success rate above 89% when using actual components.

Applying Optoelectronic Devices Fusion in Machine Vision

Machine vision is supported and enhanced by optoelectronic devices, the output from a machine vision system is information about the content of the optoelectronic signal, it is the process whereby a machine, usually a digital computer and/or electronic hardware automatically processes an optoelectronic signal and reports what it means. Machine vision methods to provide spatial coordinates measurement has developed in a wide range of technologies for multiples fields of applications such as robot navigation, medical scanning, and structural monitoring. Each technology with specified properties that could be categorized as advantage and disadvantage according its utility to the application purpose. This chapter presents the application of optoelectronic devices fusion as the base for those systems with non-lineal behavior supported by artificial intelligence techniques, which require the use of information from various sensors for pattern recognition to produce an enhanced output.

CMOS Image Sensor

In the image sensing optical receiver, such as CMOS Image Sensors (CIS), in general, comprise of photodiode and analog-mixed -signal circuits to amplify small photocurrent into digital signals. The CMOS image sensors are now the technology of choice for most imaging applications, such as digital video cameras, scanner and numerous other. Even though their sensitivity does not reach the one of the best actual CCD's (whose fill factor is about 100%), they are now commonly used because of their multiple functionalities and their easy fabrication. CMOS analog-mixed -signal circuits play a very important role for CMOS image sensors. This chapter will present the recent works on the CMOS analog-mixed -signal circuit for image sensing application, particularly for device related to machine vision application. A review of designing aspect of CIS are done. A proposed light integrating CIS was developed and measured.

Machine Vision Optical Scanners for Landslide Monitoring

An application of landslide monitoring using optical scanner as vision system is presented. The method involves finding the position of non-coherent light sources located at strategic points susceptible to landslides. The position of the light source is monitored by measuring its coordinates using a scanner based on a 45° sloping surface cylindrical mirror. This chapter also provides a background about the concept of landslides and technologies for monitoring. finally, the results of experiments of position light source monitoring in laboratory environment using the proposed method are presented.