Image Segmentation from Texture Measurement

It is known that the human visual system, unsurpassed in its ability to reconstruct surfaces, employs different cues to solve this difficult task. The prevailing method in digital photogrammetry is stereopsis. However, texture may provide valuable information about the shape of surfaces. In this paper we employ Laws' method of texture energy transforms to extract texture information from digital aerial imagery. The images are convolved with micro-texture filt~rs to obtain local texture properties. Each micro-texture feature plane is transformed into an texture energy image by nlOving-window to render macro-texture features. Finally, the macro-texture feature planes are combined and then clustered into regions of similar texture pattern. The method is implemented in a scale-space approach, and the boundaries obtained from texture are compared with physical boundaries of the image.