Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.v.

Friedrich-Alexander-Universitat Erlangen-Nürnberg

Walter Hanke Mechanische Werkstatten Gmbh & Co. Kg

Klaus Spinnler

Thomas Wittenberg

Andreas Kuleschow

Robert Couronné

Stephan Rupp

Heinz Gerhaeuser

Matthias Elter

Christian Muenzenmayer

Christian Winter

Robert Couronne

Christian Münzenmayer

Cornelia Arnold

Volker Daum

Robert Schmidt

Heiko Kuziela

Matthias Grobe

Yannick Caulier

An illumination apparatus for an image sensor at the distal end of an endoscope includes an illumination carrier and a plurality of micro LEDs each including a main surface from which the emission is made, with a maximum lateral dilatation of less than 500 &#x3bc;m. The illumination carrier is associated with the distal end of the endoscope, and the plurality of micro LEDs are arranged on the illumination carrier such that with electrical excitation, the environment of the distal end of the endoscope is at least in some portions illuminated.

Illumination apparatus for an image sensing means at the distal end of an endoscope

A method for detecting an object on an image representable by picture elements includes: 'determining first and second adaptive thresholds for picture elements of the image, depending on an average intensity in a region around the respective picture element', 'determining partial objects of picture elements of a first type that are obtained based on a comparison with the first adaptive threshold', &#x201c;determining picture elements of a second type that are obtained based on a comparison with the second adaptive threshold&#x201d; and &#x201c;combining a first and a second one of the partial objects to an extended partial object by picture elements of the second type, when a minimum distance exists between the first and the second of the partial objects, wherein the object to be detected can be described by a sum of the partial objects of picture elements of the first type and/or the obtained extended partial objects&#x201d;.

Method and apparatus for detecting objects

The invention relates to a method and device for recognizing a coin by using the embossed pattern characteristics thereof. For this purpose, the inventive method comprises in spreading the characteristics of the picture, in reducing said characteristics by reducing said picture and in transforming it by polar transformation, in comparing the transformed picture with a plurality of reference patterns according to a first simplified criterion, in creating a list of the reference patterns, in sorting them according to the similarity thereof with the transformed picture and in comparing the transformed picture with the reference patterns contained in the list according to the sorting thereof upon a second exact criterion.

Method and device for recognizing a coin by using the embossed pattern thereof

An image free from interfering structures may be generated by means of a fiber bundle of several optical fibers, when for the system of fiber bundle and sensor imaging parameters are provided, which describe the geometrical characteristics of the intensity course generated by each individual optical fiber on the sensor. In image reconstruction, for each individual optical fiber an amplitude value and/or luminosity information may be generated by fitting a function of the amplitude value and the imaging parameters of the respective optical fiber to an intensity picture of the sensor, so that an optimum amplitude and/or luminosity value may be generated considering the geometrical imaging characteristics for each individual optical fiber.

Method and device for generating a structure-free fiberscopic picture

A method for the analysis of a biological sample for determining a change thereof relative to a healthy biological sample includes creating a first image of the biological sample at a first acquisition modality and creating a second image of the biological samples at a second acquisition modality. The first image is classified on the basis of a first pre-determined parameter, and the second image is classified on the basis of a second pre-determined parameter, the first image being classified independently of the second image. Then, depending on the classification results, it is determined if the biological sample comprises a change relative to a healthy biological sample.

Method for analyzing a biological sample

In a method for extracting texture features from a multichannel image, which comprises a plurality of pixels, information of at least two channels of the image is combined for each of the plurality of pixels, and one or several texture features are determined from the combined pixel information.

Method for extracting texture features from a multichannel image

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Erlangen, Germany

Klaus Spinnler