Abstract: A method in image processing for detection of a change in the scene in an area. The method comprises the steps of recording a digital image of the area using a sensor and transforming the recorded image by an operator. The operator is based on a previous modeling of changes in the lighting in the area and on a modeling of how the sensor depicts the area in grayscale values in the recorded image. The method further comprises the step of comparing the transformed image with a reference image of the area in order to detect a difference that indicates a change in the scene.

Abstract: The present invention relates to the segmentation of two-dimensional gel electrophoresis images (2D images). The method according to the invention associates an initial protein seed candidate with an interface circumscribing said seed and thereafter brings said interface to evolve in accordance with a defined speed function F(x, y). The evolution of the interface is halted by a stopping criterion, C. According to the invention, the speed function can depend on a wide variety of parameters such as the pixel intensity, the curvature of the pixel intensity, the distance to the initial seed, the curvature and/or shape and/or normal direction and/or position of the evolving interface. The stopping criterion depends e.g. on the speed function F and/or the time of arrival T(x, y) and/or the departure time Td for said interface. The invention provides criteria for a specific treatment of saturated spots and to mike sure that interfaces never overlap.

Abstract: Method for processing digital image data for a two-dimensional array of sample substance spots and marker substance spots in an electrophoresis gel by using landmark substances having predefined properties, comprising the steps of:generating an ideal image represented by co-ordinate data corresponding to ideal positions of the marker substance spots in said array dependent on electrophoresis conditions; generating a marker image represented by co-ordinate data corresponding to detected positions of said marker substances spots in the array; determining a mathematical relation between the ideal image and the marker image, such that the co-ordinate data of said images are mapped onto each other; generating a sample image represented by a sample image data set corresponding to detected signal values in the gel; and normalising the sample image by transforming it dependent on said mathematical relation.

Abstract: A method for monitoring a monitored area comprising the steps of recording an image of the monitored area and of comparing the recorded image with a reference image in order to determine whether there is an alarm situation. The method further comprises the step of creating the reference image by combining at least two previously stored images from a set of images, so that the lighting conditions in the reference image are adjusted to the lighting conditions in the recorded image.

Abstract: A method in image processing for detection of a change in the scene in an area. The method comprises the steps of recording a digital image of the area using a sensor and transforming the recorded image by an operator. The operator is based on a previous modeling of changes in the lighting in the area and on a modeling of how the sensor depicts the area in grayscale values in the recorded image. The method further comprises the step of comparing the transformed image with a reference image of the area in order to detect a difference that indicates a change in the scene.

Abstract: A method for monitoring a monitored area comprising the steps of recording an image of the monitored area and of comparing the recorded image with a reference image in order to determine whether there is an alarm situation. The method further comprises the step of creating the reference image by combining at least two previously stored images from a set of images, so that the lighting conditions in the reference image are adjusted to the lighting conditions in the recorded image.

Abstract: An image registration (alignment) system which achieves alignment by determining an optimal focus for a composite image produced from the combination of misregistered images. The system also uses optimal or nearly optimal linear filters for filtering the combined image to emphasize (enhance) alignment information in the combined image and to de-emphasize (damp) noise. One set of the nearly optimal linear filters are modified second order difference filters in which the number of internal zeros are modified to tune the filter to the particular equipment.