Abstract: In an image processing system a processor is configured to perform an image processing method. The method performs receiving a spectral image of a person's skin and identifying the person based on the received spectral image of the person's skin and skin reflectance information.

Abstract: In an image processing system a processor is configured to perform an image processing method. The method performs receiving a spectral image of a person's skin and identifying the person based on the received spectral image of the person's skin and skin reflectance information.

Abstract: A method for applying histogram equalization to an image comprises calculating a histogram of at least one image portion of an input image to obtain histogram data representing the number of occurrences of different brightness values in said at least one image portion. Said histogram data is filled up such that substantially all brightness values have a minimum number of occurrences. A cumulative distribution function is calculated from said filled up histogram data and is equalized in a predetermined range. Finally, said at least one image portion of the input image is remapped based on said equalized cumulative distribution function.

Abstract: A method for applying histogram equalization to an image comprises calculating a histogram of at least one image portion of an input image to obtain histogram data representing the number of occurrences of different brightness values in said at least one image portion. Said histogram data is filled up such that substantially all brightness values have a minimum number of occurrences. A cumulative distribution function is calculated from said filled up histogram data and is equalized in a predetermined range. Finally, said at least one image portion of the input image is remapped based on said equalized cumulative distribution function.

Abstract: A method for converting an image and an image conversion unit are provided, the method comprising: determining a target pixel of pixels of the image; calculating a first value based on pixel values of a first set of pixels, wherein the first set of pixels do not include pixels in a column of the target pixel; determining a second value based on pixel values of a second set of pixels, wherein the second set of pixels are located in the column of the target pixel; and determining a pixel value of the target pixel based on adding the first and second values. The method and the image conversion unit are used e.g. for converting an image in interlaced format to progressive scan format.

Abstract: A method for converting an image and an image conversion unit are provided, the method comprising: determining a target pixel of pixels of the image; calculating a first value based on pixel values of a first set of pixels, wherein the first set of pixels do not include pixels in a column of the target pixel; determining a second value based on pixel values of a second set of pixels, wherein the second set of pixels are located in the column of the target pixel; and determining a pixel value of the target pixel based on adding the first and second values. The method and the image conversion unit are used e.g. for converting an image in interlaced format to progressive scan format.

Abstract: According to the present invention, for connecting the different bus systems to each other to build a superior network, a common network layer is provided to which the bus systems are connected for data and/or control exchange via gateway devices. Further, an intelligent gateway according to the present invention is distributed in the network, i.e. on the common network layer to which the gateway devices according to the present invention are connected. So this intelligent gateway can be accessed on all gateway devices. This allows the incorporation of cheap (dumb) gateway devices, which just provide the bus API, i.e. a bus service interface. Device specific (software) modules can run distributed on other intelligent gateway devices or on the intelligent gateway.