Color Image Segmentation Using Vector Quantization Techniques

In this paper we introduce vector quantization based segmentation approach that is specifically designed to segment low-altitude aerial images, as a preprocessing step to 3D reconstruction. This approach uses color similarity and volume difference criteria to merge adjacent regions. Experiments performed with real aerial images of varied nature demonstrate that this approach does not result in over segmentation or under segmentation allowing large-scale urban scenes to be segmented in an accurate, reliable and fully automatic way. The vector quantization seems to give far better results as compared to conventional on-the-fly watershed algorithm.