Robot handling of flat textile materials

The authors present a robotic system incorporating vision and force/torque sensing for handling flat textile materials and describe the results of experiments to measure the accuracy and reliability of the system for a variety of representative handling tasks for textile materials     

A cherenkov imaging technique for the detection of high energy gamma-rays

Results on the detection of high energy gamma-rays with a gas Cherenkov imaging technique are reported. The experiment conducted with a 480 MeV gamma-ray beam used a position sensitive needle array as the focal detector. Although the average number of UV photons recorded per image is quite low in this experiment ( 1.2 on average), positive results are obtained concerning unambiguous signatures of Cherenkov emission. An angular resolution of 1.4° for 480 MeV gamma-rays is also estimated.     

The Use of Boolean Model for Texture Analysis of Grey Images

We generalize here the use of the 1D Boolean model for the analysis of grey level textures. Each grey image is first split into eight binary images using different criteria. Each of these binary images is separately analysed with the help of the 1D Boolean model and features are extracted from it. The final grey texture recognition is performed on the basis of these features using several classification criteria. Experiments have been carried out using an image database of 30 grey level textures, all of them with 512×512 pixels in size, obtaining correct classification rates between 95% and 100%, according to the classification criterion used.     

Perceptual correction for colour grading of random textures

We present a method of colour shade grading for industrial inspection of random textures, the differences of which are at the threshold of human perception. This method uses image restoration techniques to recover an unblurred version of the image, and then blurs it the same way as the human visual system does, to emulate the process of the image being captured by the human sensor. Subsequently, the colour image is transformed into a perceptually uniform colour space, where colour gra ding takes place. Received: 10 October 1998 / Accepted: 21 March 2000     

Data mining for large scale 3D seismic data analysis

The automation of the analysis of large volumes of seismic data is a data mining problem, where a large database of 3D images is searched by content, for the identification of the regions that are of most interest to the oil industry. In this paper we perform this search using the 3D orientation histogram as a texture analysis tool to represent and identify regions within the data, which are compatible with a query texture.     

Structural matching in computer vision using probabilisticrelaxation

In this paper, we develop the theory of probabilistic relaxation for matching features extracted from 2D images, derive as limiting cases the various heuristic formulae used by researchers in matching problems, and state the conditions under which they apply, We successfully apply our theory to the problem of matching and recognizing aerial road network images based on road network models and to the problem of edge matching in a stereo pair. For this purpose, each line network is represented by an attributed relational graph where each node is a straight line segment characterized by certain attributes and related with every other node via a set of binary relations     

Fatigue Behavior of RC Beams Strengthened with GFRP Sheets

The objective of the presented study is to examine the effects of glass fiber reinforced polymer (GFRP) composite rehabilitation systems on the fatigue performance of reinforced concrete beams. Experiments were conducted on beams with and without GFRP composite sheets on their tensile surfaces. The specimens were 152 × 152 × 1,321 mm reinforced concrete beams with enough transverse reinforcement to avoid shear failure. The results of this study indicate that the fatigue life of reinforced concrete beams with the given geometry, subjected to the same cycling load, can be significantly extended through the use of externally bonded GFRP composite sheets. An interesting finding is that, although the fiber strengthening system increases the fatigue life of the beams, the failure mechanism, fatigue of the steel reinforcement, remains the same in both strengthened and nonstrengthened beams. Thus, it is possible to predict the fatigue life of a cyclically loaded beam using existing fatigue models.     

Cost-Based Target Selection Techniques Towards Full Space Exploration and Coverage for USAR Applications in a Priori Unknown Environments

Full coverage and exploration of an environment is essential in robot rescue operations where victim identification is required. Three methods of target selection towards full exploration and coverage of an unknown space oriented for Urban Search and Rescue (USAR) applications have been developed. These are the Selection of the closest topological node, the Selection of the minimum cost topological node and the Selection of the minimum cost sub-graph. All methods employ a topological graph extracted from the Generalized Voronoi Diagram (GVD), in order to select the next best target during exploration. The first method utilizes a distance metric for determining the next best target whereas the Selection of the minimum cost topological node method assigns four different weights on the graph’s nodes, based on certain environmental attributes. The Selection of the minimum cost sub-graph uses a similar technique, but instead of single nodes, sets of graph nodes are examined. In addition, a modification of A* algorithm for biased path creation towards uncovered areas, aiming at a faster spatial coverage, is introduced. The proposed methods’ performance is verified by experiments conducted in two heterogeneous simulated environments. Finally, the results are compared with two common exploration methods.     

Reverse engineering the way humans rank textures

We argue that in order to understand which features are used by humans to group textures, one must start by computing thousands of features of diverse nature, and select from those features those that allow the reproduction of perceptual groups or perceptual ranking created by humans. We use the Trace transform to produce such features here. We compare these features with those produced from the co-occurrence matrix and its variations. We show that when one is not interested in reproducing human behaviour, the elements of the co-occurrence matrix used as features perform best in terms of texture classification accuracy. However, these features cannot be “trained” or “selected” to imitate human ranking, while the features produced from the Trace transform can. We attribute this to the diverse nature of the features computed from the Trace transform.