# Image Processing

**Topics:**Image processing, Pixel, Digital image

**Pages:**5 (1247 words)

**Published:**July 10, 2013

Ph: 9159970702

SRI SAKTHI INSTITUTE OF ENGINEERING AND TECHNOLOGY,

COIMBATORE-641062

Email:yuvarajdoit@gmail.com

ABSTRACT:

Our paper tries to completely automate the poultry process by continuously monitoring the chickens in the poultry and by the application of image processing, identify the dead chicken using a camera and inform the appropriate person so that the dead chicken can be removed from the corresponding cabin. The chickens will be monitored in each cabin with a regular time interval. In the initial phase the background image of the cabin is stored as the reference and after say 15 minutes another image is taken and stored. The difference image is calculated for each image by the application of image subtraction. For this we employ any of the following two algorithms: 1. Two dimensional cross correlation algorithm

2. Sum of absolute difference (SAD) algorithm If there is a constant variation in the sum of pixels calculated even after 2 or 3 comparisons, then the particular cabin is said to contain a dead chicken. Considering this practical problem a solution using digital image processing is suggested. A system is developed such that the sick or the dead chicken is identified by an image processing system. The image processing tool box and image acquisition toolbox of MATLAB 7.0 are used to check motion detection in the poultry. Two algorithms that are used for motion detection are 2-D cross correlation and sum of absolute difference algorithm. A paper was designed and developed to identify the dead chicken in the poultry using a webcam, which will be connected to the Universal Serial Bus OVERVIEW

Our paper covers the following topics:

Introduction to digital image processing

Introduction to image processing in MATLAB 7.0

Steps to be followed for the dead chicken identification Software implementation

Two dimensional cross correlation algorithm

Sum of absolute difference(SAD) algorithm

Isolation of dead chicken

Conclusion

Introduction to digital image processing:

Digital image processing remains a challenging domain of programming for several reasons .First the issue of digital image processing appeared relatively late in the computer history. Secondly, digital image processing requires the most careful optimizations and especially for real time applications. Finally, digital image processing is by definition, a two dimensional domain. The original and basic way of representing a digital colored image in computers is obviously a bitmap. A bit map is constituted of rows of pixels, contraction of the words ‘Picture Element’. Each pixel has a particular value which determines the appearing color. This value is qualified by three numbers giving the decomposition of the color in the three primary colors RED, GREEN, BLUE. Any color visible to the human can be represented this way. There are about 16.8 million colors can be formed by using this RGB combination (256*256*256). This large number of colors cannot be processed by the devices which are available. So we are needed to make these colors into gray format which has only two values. Image processing Operations:

Image processing Operations can be roughly divide into three main categories: Image Compression:

Image Enhancement and restoration:

Measurement Extraction:

Introduction to image processing in MATLAB 7.0:

The image processing toolbox is a collection of functions that extend the capability of the MATLAB numeric computing environment.MATLAB stores most images as 2-D arrays (i.e., is in the form of matrices), in which each element corresponds to a single pixel in the displayed image. There are 4 basic types of...

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