Related Research

In this section we review several systems developed based on barcode, mobile phones and image recognition technologies.

1.5.1

MyMobiHalal  2.0:  Malaysian  Mobile  Halal  Product  Verification  using  Camera Phone Barcode Scanning and MMS. 

Junaini and Abduallah developed a system to automatically scan barcode to recognize Halal food (food can be eaten by Muslims) using mobile phones [11]. This research describes a mobile-based support application that can be used only by Muslims to identify the Halal status (prepared in accordance to Islamic law) of the product using mobile device.

The application requires the user to have a mobile phone with minimum of one mega pixel camera resolution for capturing the barcode image. The application server is central in this project. The database of Halal products is stored in the application server. This server also provides a platform for barcode recognition process. The barcode images sent by the consumer will go through the application server and to be processed. Then, the recognized barcode number is being used to determine Halal products for Muslims. The main objective of this project is to enhance the user input from SMS to MMS.

1.5.2 A Barcode­Scanner Aid For Visually­Impaired People. 

Visually-impaired people living independently face problems in determining the contents of packaged foods, both at home and when shopping in modern, ‘self-service’ stores. This work was aimed at assessing the feasibility of using product barcodes as an aid to the identification of package contents [12]. This work reported here was prompted by a member of the public, who contacted the University of Southampton with the suggestion that the barcode technology widely used in the food vending industry might also be used to help visually-impaired people identify the contents of food packages and developed such a device “ A scanning device” which could read barcodes and output information about package contents in synthetic speech or tactile form was seen as potentially useful in both the home context and for food shopping.

1.5.3  Information  Management  System  of  Grocery  Production  Processing  Based on a Bar Code Identification Technology. 

This system brings forward with a method of adopting a bar code technology which is successfully applied to a production processing information management of a grocery enterprise [13].

Barcode technology has widely been applied in materiel management of production processing. As people are familiar with, car, television and mobile phone etc. are composed from much different hardware and each of hardware has an exclusive identification code followed, and that the number, the shape and the estate of the hardware do not happen to change during the whole production processing.

A terminal product is made up of much hardware by different craftwork flow [6]. It is easier to adopt barcode technology to practise the production processing management when the terminal product (such as television, mobile phone etc.) is made up of standard hardware. How to effectively manage the production processing and analyze the devotion and the output of materiel is a problem that a grocery enterprise all along wants to resolve when the product (such as biscuit etc.) crank out of non-standard materials.

1.5.4 Barcode Readers using the Camera Device in Mobile Phones. 

This system shows new algorithms and the implementations of image reorganization for EAN/QR barcodes in mobile phones. The mobile phone system consists of a camera, mobile application processor, digital signal processor (DSP), and display device, and the source image is captured by the embedded camera device [14].

The camera device and application processor are necessary hardware components for this system. The application processor is needed to implement the camera interface, LCD controller, DSP for image processing, and application host CPU for real-time computations. The application processor works for displaying of the menu and preview in the display and computing of code recognition and decoding in real-time. With these systems, the user can control the position of the camera and decide the capture timing. The processing flow is as follows.

1. Execute the barcode reader application: The application processor is changed into barcode reader mode by user menu selection.

2. Capture from embedded camera device: The source images are captured by the embedded camera device via the camera interface, and these images are sent to two units, the DSP for image processing and the LCD controller for displaying the user preview.

3. Process the image in DSP: The code is detected and processed in the DSP from the captured source image, and the processed image in this phase is output as the normalized size and binarized image of the code area.

4. Decode the code: the processed code data in the previous phase is decoded in the host CPU, and the decoded code is derived to the application software.

5. Display the results: the host application displays the decoded results.

The introduced algorithm is based on the code area found by four corners detection for 2D barcode and spiral scanning for 1D barcode using the embedded DSP. This algorithm is robust for practical situations and the DSP has good enough performance for the real-time recognition of the codes.

1.5.5  Toolkit  for  Bar  Code  Recognition  and  Resolving  on  Camera  Phones  ­  Jump­Starting the Internet of Things. 

Robert Adelmann , Marc Langheinrich and Christian Flörkemeier have developed a freely available EAN-13 bar code recognition and information system that is both lightweight and fast enough for the use on camera equipped mobile phones, thus significantly lowering the barrier for large-scale, realworld testing of novel information and interaction applications based on ''connected'' physical objects [3]. A toolkit consisting of: a J2ME client for the barcode recognition on the camera phones, and a server for linking the recognized product code to free databases on the internet.

1.5.6 Research  and  Application  of  the  EAN­13  Barcode  Recognition  on  Iphone. 

College of Computer Science and Technology Sichuan University in Chengdu, Sichuan Province, P.R.CHINApresents an image processing algorithmwhich relies on knowledge about structure and appearance of IDbarcodes. It is capable of interpreting a particular type ofbarcode, called EAN-13, take by the camera phone. Theircontribution is an algorithm which is both fast and robust. In the future, we will focus on two things to make the barcode recognition more accurate and useful: one is improving the algorithm to shorten the decoding time; the other is establishing a shopping guide platform by using the barcode as a key to allow users to easily search and update the goods information [15].