Digital colour cameras are dramatically falling in price, making them a ordable for ubiquitous appliances in many applications. Change in colour perception with changing light conditions induce errors that may escape a user's awareness. Colour constancy algorithms are based on inferring light properties (usually the white point) to correct colour. Other attempts using more data for colour correction such as (ICC based) colour management characterise a capturing device under given conditions through an input device pro le. This pro le can be applied to correct for deviating colour perception. But this pro le is only valid for the speci c conditions at the time of the characterisation, but fails with changes in light. This research presents a solution to the problem of long time observations with changes in the scene's illumination for common natural (overcast or clear, blue sky) and arti cial sources (incandescent or uorescent lamps). Colour measurements for colour based reasoning need to be represented in a robustly de ned way. One such suitable and well de ned description is given by the CIE LAB colour space, a device-independent, visually linearised colour description. Colour transformations using ICC pro le are also based on CIE colour descriptions. Therefore, also the corrective colour processing has been based on ICC based colour management. To verify the viability of CIE LAB based corrective colour processing colour constancy algorithms (White Patch Retinex and Grey World Assumption) have been modi ed to operate on L a b colour tuples. Results were compared visually and numerically (using colour indexing) against those using the same algorithms operating on RGB colour tuples. We can take advantage of the fact that we are dealing with image streams over time, adding another dimension usable for analysis. A solution to the problem of slowly changing light conditions in scenes with a static camera perspective is presented. It takes advantage of the small (frame-to-frame) changes in appearance of colour within the scene over time. Reoccurring objects or (background) areas of the scene are tracked to gather data points for an analysis. As a result, a suitable colour space distortion model has been devised through a rst order Taylor approximation (a ne transformation). By performing a multidimensional linear regression analysis on the tracked data points, parameterisations for the a ne transformations were derived. Finally, the device pro le is updated by amalgamating the corrections from the model into the ICC pro le for a single, comprehensive transformation. Following applications of the ICC based colour pro les are very fast and can be used in real-time with the camera's capturing frame rate (for current normal web cameras and low spec desktop computers). As light conditions usually change on a much slower time scale than the capturing rate of a camera, the computationally expensive pro le adaptation generally showed to be usable for many frames. The goal was to set out and nd a solution for consistent colour capturing using digital cameras, which is capable of coping with changing light conditions. Theoretical backgrounds and strategies for such a system have been devised and implemented successfully.

Digital colour cameras are dramatically falling in price, making them a ordable for ubiquitous appliances in many applications. Change in colour perception with changing light conditions induce errors that may escape a user's awareness. Colour constancy algorithms are based on inferring light properties (usually the white point) to correct colour. Other attempts using more data for colour correction such as (ICC based) colour management characterise a capturing device under given conditions through an input device pro le. This pro le can be applied to correct for deviating colour perception. But this pro le is only valid for the speci c conditions at the time of the characterisation, but fails with changes in light. This research presents a solution to the problem of long time observations with changes in the scene's illumination for common natural (overcast or clear, blue sky) and arti cial sources (incandescent or uorescent lamps). Colour measurements for colour based reasoning need to be represented in a robustly de ned way. One such suitable and well de ned description is given by the CIE LAB colour space, a device-independent, visually linearised colour description. Colour transformations using ICC pro le are also based on CIE colour descriptions. Therefore, also the corrective colour processing has been based on ICC based colour management. To verify the viability of CIE LAB based corrective colour processing colour constancy algorithms (White Patch Retinex and Grey World Assumption) have been modi ed to operate on L a b colour tuples. Results were compared visually and numerically (using colour indexing) against those using the same algorithms operating on RGB colour tuples. We can take advantage of the fact that we are dealing with image streams over time, adding another dimension usable for analysis. A solution to the problem of slowly changing light conditions in scenes with a static camera perspective is presented. It takes advantage of the small (frame-to-frame) changes in appearance of colour within the scene over time. Reoccurring objects or (background) areas of the scene are tracked to gather data points for an analysis. As a result, a suitable colour space distortion model has been devised through a rst order Taylor approximation (a ne transformation). By performing a multidimensional linear regression analysis on the tracked data points, parameterisations for the a ne transformations were derived. Finally, the device pro le is updated by amalgamating the corrections from the model into the ICC pro le for a single, comprehensive transformation. Following applications of the ICC based colour pro les are very fast and can be used in real-time with the camera's capturing frame rate (for current normal web cameras and low spec desktop computers). As light conditions usually change on a much slower time scale than the capturing rate of a camera, the computationally expensive pro le adaptation generally showed to be usable for many frames. The goal was to set out and nd a solution for consistent colour capturing using digital cameras, which is capable of coping with changing light conditions. Theoretical backgrounds and strategies for such a system have been devised and implemented successfully.

Digital colour cameras are dramatically falling in price, making them a ordable for ubiquitous appliances in many applications. Change in colour perception with changing light conditions induce errors that may escape a user's awareness. Colour constancy algorithms are based on inferring light properties (usually the white point) to correct colour. Other attempts using more data for colour correction such as (ICC based) colour management characterise a capturing device under given conditions through an input device pro le. This pro le can be applied to correct for deviating colour perception. But this pro le is only valid for the speci c conditions at the time of the characterisation, but fails with changes in light. This research presents a solution to the problem of long time observations with changes in the scene's illumination for common natural (overcast or clear, blue sky) and arti cial sources (incandescent or uorescent lamps). Colour measurements for colour based reasoning need to be represented in a robustly de ned way. One such suitable and well de ned description is given by the CIE LAB colour space, a device-independent, visually linearised colour description. Colour transformations using ICC pro le are also based on CIE colour descriptions. Therefore, also the corrective colour processing has been based on ICC based colour management. To verify the viability of CIE LAB based corrective colour processing colour constancy algorithms (White Patch Retinex and Grey World Assumption) have been modi ed to operate on L a b colour tuples. Results were compared visually and numerically (using colour indexing) against those using the same algorithms operating on RGB colour tuples. We can take advantage of the fact that we are dealing with image streams over time, adding another dimension usable for analysis. A solution to the problem of slowly changing light conditions in scenes with a static camera perspective is presented. It takes advantage of the small (frame-to-frame) changes in appearance of colour within the scene over time. Reoccurring objects or (background) areas of the scene are tracked to gather data points for an analysis. As a result, a suitable colour space distortion model has been devised through a rst order Taylor approximation (a ne transformation). By performing a multidimensional linear regression analysis on the tracked data points, parameterisations for the a ne transformations were derived. Finally, the device pro le is updated by amalgamating the corrections from the model into the ICC pro le for a single, comprehensive transformation. Following applications of the ICC based colour pro les are very fast and can be used in real-time with the camera's capturing frame rate (for current normal web cameras and low spec desktop computers). As light conditions usually change on a much slower time scale than the capturing rate of a camera, the computationally expensive pro le adaptation generally showed to be usable for many frames. The goal was to set out and nd a solution for consistent colour capturing using digital cameras, which is capable of coping with changing light conditions. Theoretical backgrounds and strategies for such a system have been devised and implemented successfully.

Digital colour cameras are dramatically falling in price, making them a ordable for ubiquitous appliances in many applications. Change in colour perception with changing light conditions induce errors that may escape a user's awareness. Colour constancy algorithms are based on inferring light properties (usually the white point) to correct colour. Other attempts using more data for colour correction such as (ICC based) colour management characterise a capturing device under given conditions through an input device pro le. This pro le can be applied to correct for deviating colour perception. But this pro le is only valid for the speci c conditions at the time of the characterisation, but fails with changes in light. This research presents a solution to the problem of long time observations with changes in the scene's illumination for common natural (overcast or clear, blue sky) and arti cial sources (incandescent or uorescent lamps). Colour measurements for colour based reasoning need to be represented in a robustly de ned way. One such suitable and well de ned description is given by the CIE LAB colour space, a device-independent, visually linearised colour description. Colour transformations using ICC pro le are also based on CIE colour descriptions. Therefore, also the corrective colour processing has been based on ICC based colour management. To verify the viability of CIE LAB based corrective colour processing colour constancy algorithms (White Patch Retinex and Grey World Assumption) have been modi ed to operate on L a b colour tuples. Results were compared visually and numerically (using colour indexing) against those using the same algorithms operating on RGB colour tuples. We can take advantage of the fact that we are dealing with image streams over time, adding another dimension usable for analysis. A solution to the problem of slowly changing light conditions in scenes with a static camera perspective is presented. It takes advantage of the small (frame-to-frame) changes in appearance of colour within the scene over time. Reoccurring objects or (background) areas of the scene are tracked to gather data points for an analysis. As a result, a suitable colour space distortion model has been devised through a rst order Taylor approximation (a ne transformation). By performing a multidimensional linear regression analysis on the tracked data points, parameterisations for the a ne transformations were derived. Finally, the device pro le is updated by amalgamating the corrections from the model into the ICC pro le for a single, comprehensive transformation. Following applications of the ICC based colour pro les are very fast and can be used in real-time with the camera's capturing frame rate (for current normal web cameras and low spec desktop computers). As light conditions usually change on a much slower time scale than the capturing rate of a camera, the computationally expensive pro le adaptation generally showed to be usable for many frames. The goal was to set out and nd a solution for consistent colour capturing using digital cameras, which is capable of coping with changing light conditions. Theoretical backgrounds and strategies for such a system have been devised and implemented successfully.

Digital colour cameras are dramatically falling in price, making them a ordable for ubiquitous appliances in many applications. Change in colour perception with changing light conditions induce errors that may escape a user's awareness. Colour constancy algorithms are based on inferring light properties (usually the white point) to correct colour. Other attempts using more data for colour correction such as (ICC based) colour management characterise a capturing device under given conditions through an input device pro le. This pro le can be applied to correct for deviating colour perception. But this pro le is only valid for the speci c conditions at the time of the characterisation, but fails with changes in light. This research presents a solution to the problem of long time observations with changes in the scene's illumination for common natural (overcast or clear, blue sky) and arti cial sources (incandescent or uorescent lamps). Colour measurements for colour based reasoning need to be represented in a robustly de ned way. One such suitable and well de ned description is given by the CIE LAB colour space, a device-independent, visually linearised colour description. Colour transformations using ICC pro le are also based on CIE colour descriptions. Therefore, also the corrective colour processing has been based on ICC based colour management. To verify the viability of CIE LAB based corrective colour processing colour constancy algorithms (White Patch Retinex and Grey World Assumption) have been modi ed to operate on L a b colour tuples. Results were compared visually and numerically (using colour indexing) against those using the same algorithms operating on RGB colour tuples. We can take advantage of the fact that we are dealing with image streams over time, adding another dimension usable for analysis. A solution to the problem of slowly changing light conditions in scenes with a static camera perspective is presented. It takes advantage of the small (frame-to-frame) changes in appearance of colour within the scene over time. Reoccurring objects or (background) areas of the scene are tracked to gather data points for an analysis. As a result, a suitable colour space distortion model has been devised through a rst order Taylor approximation (a ne transformation). By performing a multidimensional linear regression analysis on the tracked data points, parameterisations for the a ne transformations were derived. Finally, the device pro le is updated by amalgamating the corrections from the model into the ICC pro le for a single, comprehensive transformation. Following applications of the ICC based colour pro les are very fast and can be used in real-time with the camera's capturing frame rate (for current normal web cameras and low spec desktop computers). As light conditions usually change on a much slower time scale than the capturing rate of a camera, the computationally expensive pro le adaptation generally showed to be usable for many frames. The goal was to set out and nd a solution for consistent colour capturing using digital cameras, which is capable of coping with changing light conditions. Theoretical backgrounds and strategies for such a system have been devised and implemented successfully.