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Research
Bar Code Recognition in Complex Scenes by Camera Phones
How to study this subject
Modern mobile phones are high resolution colour displays, they support
different standards of wireless networking, and they have reasonable
processing power. Although still primarily used for voice communication,
with the inclusion of digital cameras these devices have become a
potential platform for machine vision application such as bar code
recognition.
In recent years, advanced technology has succeeded in continuously producing smaller yet smarter devices.Now mobile phones can implement many new kinds of applications such as taking photos, and movie shooting by using embedded camera devices. So an interesting approach is capturing bar code with their cameras and decoding them withsoftware running on the phoneIn August 2006, 82.4 percent of the respondents whohad camera phones with QR Code (Quick Response Code) readers used camera phones with QR Code. But previous research work has shown that recognition of 2D barcode in mobile phone is very difficult because of the high noise, non-uniform illumination, skew distortion, low resolution and optical blur. It is very difficult to robustly extract accurate features such as edges and peaks of the bars and spaces from the barcode images taken by a camera phone.
Many new algorithms are presented for dealing with 1D bar code in complex situation.Ohbuchi et al.presented an algorithm capable of the real-time recognition of barcodes on a mobile phone.Sun et al.introduce an algorithm to analyze and correct the distorted image of QR Code. The algorithm includes gray-scale image transformation, binary image, canny edge detection, external contours finding, inverse perspective transformation and cell grids generating. In this method, binary image and edge detection is very important for following decode. But it is very difficult to binaries image and extract accurate edge in the blurred and damaged bar code images. Here we describe a new image recognition algorithm which applied to capture image in various light condition.
WHY USE MOBILE PHONE
BAR CODE READERS
Too Expensive Scanners.
Have No Other Use.
Too Bulky.
Workers Have To Be Trained.
MOBILE PHONES
Affordable Prices And Common.
Have Various Uses.
Too Handy.
No Training.
DATA MATRIX
Data matrix is one of the most well known 2D bar code standards. It is widely used in the automotive, aerospace and computer manufacturing industries, for large data capacity labelling, such as direct part marking and package marking.
It consist of a solid- line locator( the two solid line), a patterned-line locator( the two alternating dark and light patterned lines), the inside area with encoded data in binary, and aquiet zone( a blank area) surrounding the whole tag.
Its capacity is 2334 alphanumeric characters or 1556 8-bit ASCII characters, encoding any data. It employs the Read- Solomon error correction to enable accurate reads even when substential pats of the code are distorted.
In recent years, advanced technology has succeeded in continuously producing smaller yet smarter devices.Now mobile phones can implement many new kinds of applications such as taking photos, and movie shooting by using embedded camera devices. So an interesting approach is capturing bar code with their cameras and decoding them withsoftware running on the phoneIn August 2006, 82.4 percent of the respondents whohad camera phones with QR Code (Quick Response Code) readers used camera phones with QR Code. But previous research work has shown that recognition of 2D barcode in mobile phone is very difficult because of the high noise, non-uniform illumination, skew distortion, low resolution and optical blur. It is very difficult to robustly extract accurate features such as edges and peaks of the bars and spaces from the barcode images taken by a camera phone.
Many new algorithms are presented for dealing with 1D bar code in complex situation.Ohbuchi et al.presented an algorithm capable of the real-time recognition of barcodes on a mobile phone.Sun et al.introduce an algorithm to analyze and correct the distorted image of QR Code. The algorithm includes gray-scale image transformation, binary image, canny edge detection, external contours finding, inverse perspective transformation and cell grids generating. In this method, binary image and edge detection is very important for following decode. But it is very difficult to binaries image and extract accurate edge in the blurred and damaged bar code images. Here we describe a new image recognition algorithm which applied to capture image in various light condition.
WHY USE MOBILE PHONE
BAR CODE READERS
Too Expensive Scanners.
Have No Other Use.
Too Bulky.
Workers Have To Be Trained.
MOBILE PHONES
Affordable Prices And Common.
Have Various Uses.
Too Handy.
No Training.
DATA MATRIX
Data matrix is one of the most well known 2D bar code standards. It is widely used in the automotive, aerospace and computer manufacturing industries, for large data capacity labelling, such as direct part marking and package marking.
It consist of a solid- line locator( the two solid line), a patterned-line locator( the two alternating dark and light patterned lines), the inside area with encoded data in binary, and aquiet zone( a blank area) surrounding the whole tag.
Its capacity is 2334 alphanumeric characters or 1556 8-bit ASCII characters, encoding any data. It employs the Read- Solomon error correction to enable accurate reads even when substential pats of the code are distorted.
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