Current scenario in computer vision demands an efficient and robust technique for facial expression recognition. There is also a need for a generalized technique that can even be used for content based image retrieval...
详细信息
Current scenario in computer vision demands an efficient and robust technique for facial expression recognition. There is also a need for a generalized technique that can even be used for content based image retrieval and analysis. This paper introduces a novel methodology of facial expression recognition using Support Vector Machines. An efficient model is trained and developed using the necessary features extracted by employing 2D Gabor filters. Practically, six different methods for handling the feature vectors are discussed and extensively analyzed in this paper. The developed model is tested and cross validated and the detailed results are presented. It is observed that the proposed method offers a consistent and good accuracy (83.3%) for all the six basic expressions considered. In addition, the implementation complexity is reduced by minimizing the number of support vectors, unlike the traditional counterparts. The proposed method shall definitely turn out to be an effective alternative for the existing methods.
Most of the classification problems frequently encounter a multi class predicament and offers a good scope for research. This paper has a comprehensive approach to the available multi-class technique using Artificial ...
详细信息
Most of the classification problems frequently encounter a multi class predicament and offers a good scope for research. This paper has a comprehensive approach to the available multi-class technique using Artificial Neural Networks and then introduces a new algorithm to overcome the demerits of the former. In addition, a new algorithm combining ANN and chameleon clustering is suggested and validated. An SVM model for the above is also proposed and sufficiently tested with a typical example i.e. Image Segmentation. Also, the permutation effects prevailing in Half -against-Half multi class algorithm of SVM is efficiently tackled by developing an algorithm using ldquocircular shift strategyrdquo and employing the same. The use of clustering methods with SVM to improve its efficiency is also discussed. All the above mentioned models are extensively analyzed and the results are presented. It is found that the proposed method is an effective alternative for existing methods and offers consistent performance.
Optical character recognition is an evergreen area of research and is verily used in various real time applications. This paper proposes a new technique of optical character recognition using Gabor filters and support...
详细信息
Optical character recognition is an evergreen area of research and is verily used in various real time applications. This paper proposes a new technique of optical character recognition using Gabor filters and support vector machines (SVM). This method proves to be very effective with the use of Gabor filters for feature extraction and SVM for developing the model. The model proposed is trained and validated for two languages - English and Tamil and the results are found to be very much encouraging. The model developed works for the entire character set in both the languages including symbols and numerals. In addition , the model can recognise the characters of six different fonts in English and Twelve different fonts in Tamil. The average accuracy of recognition for English is 97% and for Tamil it is 84%, which is achieved in just three iterations of training. The method can turn out to be a suitable candidate for future applications in this area.
Optical character recognition (OCR) is a classical research field and has become one of most thriving applications in the field of pattern recognition. Feature extraction is a key step in the process of OCR, which in ...
详细信息
Optical character recognition (OCR) is a classical research field and has become one of most thriving applications in the field of pattern recognition. Feature extraction is a key step in the process of OCR, which in fact is a deciding factor of the accuracy of the system. This paper proposes a novel and robust technique for feature extraction using Gabor Filters, to be employed in the OCR. The use of 2D Gabor filters is investigated and features are extracted using these filters. The technique generally extracts fifty features based on global texture analysis and can be further extended to increase the number of features if necessary. The algorithm is well explained and is found that the proposed method demonstrated better performance in efficiency. In addition, experimental results show that the method gains high recognition rate and cost reasonable average running time.
暂无评论