現代人因工作忙碌或生活壓力大導致三餐飲食不正常與隨意的攝取許多不健康的速食食物,而忽略了人體應該所攝取的營養物,近而造成身體上的病變。 而本論文提出新的二維條碼影像處理模組,並在320×240攝影機最小畫面下作擷取不同焦距距離下的影像及搜尋發現者圖式(Finder Pattern)定位出圖像的位置,並利用本論文所提出的基本單位比例式轉換CROBU(Conversion ratio of basic unit)方法,轉化二維條碼為像素一的比例大小做影像比對,之後經由影像比對的方法來判別二維條碼的判別率,一般在讀取二維條碼都是利用解碼軟體來做辨識的動作,而本篇論文是利用影像比對的方法去判別二維條碼與提升執行的速度及判別率。 依本篇論文所提的二維條碼影像處理模組,的確可以在複雜的背景下擷取及正規化毛邊圖像,使二維條碼判別率加以提升,而本研究最主要是提供人體攝取營養物之管理與建議平台,二維條碼的快速反應碼(Quick Response Code)圖像表示維生素與卡路里量的資訊,透過MATLAB 與 CCD Camera 即時拍攝二維條碼去計算出你現在所攝取的食物是有哪些營養物,在建議你應該攝取哪些食材,以達到健康管理的效應。
Modern worker are so busy and suffering from lots of stresses, leading to abnormal diet and intake many unhealthy foods, while ignoring that the human should be taking nutrients to avoid causing physical disease. 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 ordeckle 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.