Browsing by Subject "Surface recognition"

Now showing 1 - 3 of 3

Open Access
A comparative analysis of different approaches to target differentiation and localization using infrared sensors
(2006) Aytaç, Tayfun
This study compares the performances of various techniques for the differentiation and localization of commonly encountered features in indoor environments, such as planes, corners, edges, and cylinders, possibly with different surface properties, using simple infrared sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the localization and differentiation process. The techniques considered include rule-based, template-based, and neural network-based target differentiation, parametric surface differentiation, and statistical pattern recognition techniques such as parametric density estimation, various linear and quadratic classifiers, mixture of normals, kernel estimator, k-nearest neighbor, artificial neural network, and support vector machine classi- fiers. The geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. For a set of six surfaces, we get a correct differentiation rate of 100% in parametric differentiation based on reflection modeling. The results demonstrate that simple infrared sensors, when coupled with appropriate processing, can be used to extract substantially more information than such devices are commonly employed for. The demonstrated system would find application in intelligent autonomous systems such as mobile robots whose task involves surveying an unknown environment made of different geometry and surface types. Industrial applications where different materials/surfaces must be identified and separated may also benefit from this approach.
Open Access
Differentiation and localization using infrared sensors
(2002-08) Aytaç, Tayfun
In this thesis different approaches for the differentiation and localization of targets using low cost infrared sensors are presented. The intensity readings obtained with such sensors are highly dependent on the location and properties of targets in a way which cannot be represented in a simple manner, making the differentiation and localization process difficult. We propose the use of angular intensity scans and present different approaches to process them. Using these approaches, targets of different geometrical shapes but identical surface properties targets of difffferent surface properties but identical geometry, and targets having both different geometrical shapes and surface properties are differentiated and localized in a position-invariant manner. Maximum correct differentiation rates of 97% 87% and 65% are respectively achieved in these cases, indicating that the geometrical properties of targets are more distinctive than their surface properties in the differentiation process. The different approaches are verified experimentally with target types of commonly encountered geometries in indoor environments and with surfaces of different reflection properties. The results indicate that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for.
Open Access
Position-invariant surface recognition and localization using infrared sensors
(SPIE, 2003) Barshan, B.; Aytaç, T.
Low-cost infrared emitters and detectors are used for the recognition of surfaces with different properties in a location-invariant manner. The intensity readings obtained with such devices are highly dependent on the location and properties of the surface in a way that cannot be represented in a simple manner, complicating the recognition and localization process. We propose the use of angular intensity scans and present an algorithm to process them. This approach can distinguish different surfaces independently of their positions. Once the surface is identified, its position can also be estimated. The method is verified experimentally with the surfaces aluminum, white painted wall, brown kraft paper, and polystyrene foam packaging material. A correct differentiation rate of 87% is achieved, and the surfaces are localized within absolute range and azimuth errors of 1.2 cm and 1.0 deg, respectively. The method demonstrated shows that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for. © 2003 Society of Photo-Optical Instrumentation Engineers.