Background Recognition in Outdoor Images Using Image Segmentation and Boundary Detection

Abstract: In this paper, my research objective is to explore detecting object boundaries in outdoor scene images solely based on some general properties of the real-world objects, such as perceptual organization laws, without depending on a priori knowledge of the specific objects. Here in order to distinguish the unstructured and structured objects in an outdoor scene, image segmentation is performed. After that the boundary of the foreground object alone is extracted. Then using sobel edge detection method all the edges in the image is detected. In the second round of grouping image fusion is performed using alpha factor which can be varied to realize the contribution of foreground and background objects. After background objects are identified, we roughly know where the structured objects are and delimit perceptual organization in certain areas of an image. This paper shows that, for many fairly articulated objects, recognition may not be a requirement for segmentation. The geometric relationships of the constituent parts of the objects provide useful cues indicating the memberships of these parts.

Keywords: POM, boundary detection, GDS and BSDS