Enhancing the recognition rate of Two-Dimensional Barcodes Image and applications

The thesis not only proposed the latest Two- Dimensional Barcodes Image-processing Module, but also captured the smallest camera screens (320×240) with different focal distances and tried to find out “Finder Pattern” for positioning images. Further, use CROBU (Conversion Ratio of Basic Unit) the thesis proposed to convert 2-D barcodes into 1-pixel ratio to match images before judging recognition rate of 2-D barcodes through matching. Normally speaking, 2-D barcodes are deciphered and recognized by software while the thesis recognizes 2-D barcodes and enhances implementation speed up to 10-cm accurate max. using image matching. The 2-D barcodes image-processing module the thesis proposed does capture and standardize image with complicated background or raw edge, which enhances 2-D barcodes recognition rate. The main point of this study is to construct a platform to manage or suggest nutrients human body needs. The Quick Response Code image of 2-D barcodes represents vitamin and calories information. 2-D barcodes taken instantly by MATLAB and CCD camera can be used to list nutrients from foods you eat recently and suggest what else you should eat for the purpose of health management.