Wolfgang Ortmann

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In this paper an approach is presented for robust shift detection of two given images. The new unifying idea is that we determine a shifted delta impulse using some well-known restoration techniques, e.g. the Wiener filtering , constraint restoration, entropy restoration, and Baysian restoration. The used restoration techniques imply the robustness of the(More)
A robust segmentation is the most important part of an automatic character recognition system (e.g. document processing , license plate recognition etc.). In our contribution we present an efficient segmentation framework using a pre-processing step for shadow suppression combined with a local thresholding technique. The method is based on a combination of(More)
The quantitative analysis of mitochondria morphology is of great interest on medical research of neurodegnerative diseases, and also for cancer disease, and Diabetis melitus. The state-of-the-art in mitochondrial analysis is based on length measurements of randomly selected individual mitochondria. As manual segmentation and evaluation for whole cell(More)
BACKGROUND The two-dimensional videographic analysis of vibrissal movements in behaving rodents has become a standard method to estimate the degree of functional impairment and recovery after facial nerve injuries quantitatively. The main limitation of the method is the time consuming, uneconomic process of manually tracking the vibrissae in video(More)
We present a fast and accurate method to compose images delivered by a quadocular document scanner into a global consistent image. The Shift Detection by Restoration (SDR) approach is used to overcome document deformations. Our method outperforms state of the art panoramic image approaches and is able to work within one second on standard hardware.
Affine point pattern matching (APPM) is an integral part of many pattern recognition problems. Given two sets P and Q of points with unknown assignments pi → qj between the points, no additional information is available. The following task must be solved: – Find an affine transformation T such that the distance between P and the transformed set Q = TQ is(More)