Alfonzo Baumgartner

Image comparison method for visual quality control based on matrix decomposition

The image processing applied on the original tile image and the replica images in serial production is used for visual quality control. The image of a tile that contains no visual quality error represents the original image. The images of the tiles from the production line that could contain some of the visual quality errors represent the replicas. The image processing is based on the image matrix decomposition method. The matrix form of the original image is transformed to a vector. The images made by the variations of a good original image are transformed to the matrix made by such vectors. Using the SVD of the matrix of variations of the original image makes the image comparison duration shorter. The number of computer operations decreases by using SVD approximation by a lower rank matrix. The SVD calculation of the matrix is done just once so that the image processing time is shorter. Too low a rank of the matrix could yield bad comparison results. The development and testing of this method are used for an early design of the computer aided visual control.

A fast work function algorithm for solving the k-server problem

This paper deals with the work function algorithm (WFA) for solving the on-line k-server problem. The paper addresses some practical aspects of the WFA, such as its efficient implementation and its true quality of serving. First, an implementation of the WFA is proposed, which is based on network flows, and which reduces each step of the WFA to only one minimal-cost maximal flow problem instance. Next, it is explained how the proposed implementation can further be simplified if the involved metric space is finite. Also, it is described how actual computing of optimal flows can be speeded up by taking into account special properties of the involved networks. Some experiments based on the proposed implementation and improvements are presented, where actual serving costs of the WFA have been measured on very large problem instances and compared with costs of other algorithms. Finally, suitability of the WFA for solving real-life problems is discussed.

Work Function Algorithm with a Moving Window for Solving the On-Line k-Server Problem

We consider a modification of the well known work function algorithm (WFA) for solving the on-line k-server problem. Our modified WFA is based on a moving window, i.e. on the approximate work function that takes into account only a fixed number of most recent on-line requests. The main motivation for using a moving window is to gain control over the prohibitive computational complexity imposed by the original algorithm. Experimental results are presented, where the performance of the modified WFA has been compared vs. the original WFA.

Work Function Algorithm with a Moving Window for Solving the On-line k-server Problem

We consider a modification of the well known work function algorithm (WFA) for solving the on-line kserver problem. Our modified WFA is based on a moving window, i. e. on the approximate work function that takes into account only a fixed number of most recent on-line requests. The main motivation for using a moving window is to gain control over the prohibitive computational complexity imposed by the original algorithm. Experimental results are presented, where the performance of the modified WFA has been compared vs. the original WFA.

Edge-preserving partial variable median filtering for fast noise reduction in CT slices

Median filter as a widespread noise reduction technique is here adapted for images taken with computed tomography (CT) scanner. In order to remove noise and thereby preserve edges and clear contours of objects we propose adapted method which uses partial variable median filtering. Except method explanation, we propose suitable platform for implementation, considering size of data set and time requirements of our method. Experimental image processing results and performance tests are shown in this paper.