One of the challenging problems of pervasive computing is to link a physical object with digital information because many of the pervasive computing applications require manual inputs or complex image processing to obtain information related to a real object. The use of 2D barcodes eliminates such excess processing to acquire the needed information. The 2D barcodes have high capacity to store data, ’ are less prone to human input error and act as a tool to acquire information on site without network access. The currently available solutions use 1D barcodes to represent dynamic information residing in a database and use 2D barcodes to represent only static information that also encode only URLs. In all such applications, ’ the source of information gets restricted to either a database or the static data encoded inside a 2D barcode. None of such solutions takes advantage of 2D barcode capabilities to collect information from different sources and attach it to the real world entity. Moreover, ’ a 2D barcode can also represent and categorize complex text information.

Our approach integrates the capabilities of 1D barcode into 2D barcode to represent and classify the complex digital information collected from different sources. We design and implement an information management system on a handheld device that has image processing and barcode decoding capabilities to address the above- –mentioned problem. Our prototype provides a generic framework to decode either 1D or 2D barcode, ’ parse the complex information (both dynamic and static) inside the 2D barcode, ’ differentiate the complex information based on content types and classify the image based on the barcode format. It also assists users in decision- –making and information analysis. An example system application can be deployed in grocery stores as a part of the enterprise information management system.