Calculating the weight of a pig through facial geometry using 2-dimensional image processing
Clark, Alexander W.
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This thesis will outline the groundwork of facial detection and recognition software to be used with pigs in order to estimate their weight from a digital image. The facial detection of the pig is achieved through identification of the features using the Viola-Jones method for cascade classifiers and basic likelihood functions. The document will cover both the general theory behind these concepts and the actual implementation as used in the software. Next, the need of transforming the newly detected pig face to be used for facial recognition is covered through perspective transformation and bicubic pixel interpolation of the facial geometries. After this, the thesis will discuss the use of local binary patterns to sort the photos of the pigs with an unsupervised clustering technique. Next, the implementation of least squares regression is covered to predict the weight of a pig from the facial features. Finally, the thesis will conclude with a discussion on the multiple error-checking and outlier correction techniques used to make the software more robust.