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Automatic crack detection on train wheel surface is highly crucial for safety and labor-cost efficiency. Algorithms have been explored to cope with the image based crack detection problem, but mostly for concrete structure or pavement surface. It's a tougher problem on train wheel surface because of noise such as scratch, rust, dirt, shadow and son on which are unlikely to be denoised by simple image...
This paper employs the interval weighted multi-template matching approach for accurate measurement. Generally, a vernier caliper is used as the subject to capture the analyzing image. However, the vernier caliper has many similar regions which all effect the measure accuracy. The traditional template matching with only one template is not suitable, as the matching region may only stands for one local...
Automatic 3D facial expression recognition is still a challenging problem. This paper proposes the variation faces combining SVM to classify 3D facial expressions automatically as the flow of generating variation faces is without any manual intervention. To validate this strategy, the Fourier spectrum feature is explored and its highest recognition rate, 85.33% represents to be comparative to most...
Determining what features are optimal for face representation is quite a challenge in Face Recognition. Joint Boosting is a strong algorithm to select important features from feature pool. And, it outperforms other feature selection methods. But it takes quite a long time to train on a large training set. In this paper, an Accelerated Joint Boosting is proposed to resolve the time wasting problem...
Determining what features are important for face representation is quite challenging in Face Recognition. Real Adaboost performs remarkably in training classifiers for object detection which is a binary classification problem. As for Face Recognition, we should transform the multi-class problem into a binary one. In this paper, a feature selection method based on Real Adaboost for Face Recognition...
This paper investigates the local Gabor filters for facial expression recognition. The local Gabor filters can not only reduce the memory requirement but also lower the time of extracting Gabor features. By contracting among the recognition rates using different local Gabor filters, we can get that not each of the Gabor filters which choose different scales can provide the same power for facial expression...
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