Battery-powered mobile systems such as PDAs (personal digital assistants) and mobile phones play an increasing role in handling visual contents such as images. Thousands of images can be stored in a mobile system with the advances in memory technology; this creates the need for better organization and retrieval of the images. Content Based Image Retrieval (CBIR) provides a method to retrieve images based on their contents. In CBIR, images are represented and compared by high-dimensional vectors called features. Loading these features into memory and comparing them consumes a significant amount of energy. In this thesis, we present the first study on energy conservation for CBIR on a mobile system. We develop an adaptive loading scheme to save energy for CBIR. Our method reduces the features to be loaded into memory for each query image. The reduction is achieved by estimating the difficulty of the query. If the images are dissimilar, fewer features are sufficient; less computation is performed and energy can be saved. For each query image, a similarity index is calculated to determine the features' length for meeting a target accuracy. Further, we consider the effect of consecutive user queries and show how features can be "cached" in memory to save energy. We implemented this algorithm on an HP iPAQ hw6945 and measured the energy savings. For a collection of 5000 images, we obtained average energy reduction of 61.3% compared to an existing CBIR implementation.

Date of this Version

July 2008


Electrical and Computer Engineering

Month of Graduation


Year of Graduation



Master of Science in Electrical and Computer Engineering

Head of Graduate Program

M.J.T. Smith

Advisor 1 or Chair of Committee

Y.H. Lu

Committee Member 1

Y.H. Lu

Committee Member 2

Mithuna Thottethodi

Committee Member 3

Vijay Raghunathan