Agglomerative hierarchical cluster analysis was used to group similar spectra from a large database of samples. Based on angles between reflectance vectors of members of a cluster, a reflectance vector was selected as representative of that cluster. Representative samples were grouped together and stored as new calibration targets. Simulated wide-band imaging with glass filters was performed us...

Calibration is one of the most important technologies for line-structured light vision sensor. The existing calibration methods depend on special calibration equipments, whose accuracy determines the calibration accuracy. It is difficult to meet the requirements of universality and field calibration with those methods. In order to solve these problems, a new calibration method based on the comb...

The analysis of vanishing points on digital images provides strong cues for inferring the 3D structure of the depicted scene and can be exploited in a variety of computer vision applications. In this paper, we propose a method for estimating vanishing points in images of architectural environments that can be used for camera calibration and pose estimation, important tasks in large-scale 3D rec...

Image segmentation is an essential issue in image description and classification. Currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. Moreover, there are many uncertainties and vagueness in images, which crisp clustering and even Type-1 fuzzy clustering could not handle. Hence, Type-...

Clustering of objects is an important area of research and application in variety of fields. In this paper we present a good technique for data clustering and application of this Technique for data clustering in a closed area. We compare this method with K-nearest neighbor and K-means.  

An optimal calibration method for a microelectro-mechanical inertial measurement unit (MIMU) is presented in this paper. The accuracy of the MIMU is highly dependent on calibration to remove the deterministic errors of systematic errors, which also contain random errors. The overlapping Allan variance is applied to characterize the types of random error terms in the measurements. The calibratio...

      A new method was developed for the spectral resolution by further determination of three- and  four-component  mixtures  of  drugs in urine samples through  the complementary application of multivariate curve resolution-alternating least squares with correlation  constraint. In the current study, a simple method was proposed to construct a calibration set for the mixture of drugs in the p...

Identifying clusters is an important aspect of data analysis. This paper proposes a noveldata clustering algorithm to increase the clustering accuracy. A novel game theoretic self-organizingmap (NGTSOM ) and neural gas (NG) are used in combination with Competitive Hebbian Learning(CHL) to improve the quality of the map and provide a better vector quantization (VQ) for clusteringdata. Different ...