A Unified Approach for Representing Outdoor Scenes

Abstract

Generalized image understanding of natural outdoor images is fundamentally a bottom-up approach guided by the data and information received from the digital input images. The importance of intermediate image representation that aids generalized image understanding, inspired the proposed a unified approach for providing a new meaningful and objective representation of a given outdoor scene. The proposed unified framework provides a novel set of string and semantic codes, based on inferential statistical data obtained from segments characterization and blocks characterization of natural outdoor images. The framework acts as an analytical tool that can categorize the input images into four types based on the inferential statistical representation - 1) Object-based image, 2) Heterogeneous color based texture image, 3) Homogeneous color based texture image, 4) Pure toned image. The proposed string and semantic code characterization is also rotation and scale variant. Such a representation is simple, unsupervised, computationally inexpensive and also places minimal demand on the storage. Later for a higher-level image analysis and understanding the proposed unified approach can provide focused interaction between the above intermediate representation and domain scene knowledge for object detection, classification, or recognition.

Keywords

• Image segmentation
• texture characterization
• image analysis
• image representation
• image blocks
• string code