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In this paper, we propose a palmprint recognition scheme using histograms of sparse codes (HSC) as a new feature for palmprint image. In the feature extraction stage, the HSC feature is obtained by computing sparse codes for a given dictionary from a palmprint image, which results in a feature image. In the feature encoding stage, a hash table is designed from the feature image using the binary hashing...
Facial recognition is a challenging problem in image processing and machine learning areas. Since widespread applications of facial recognition make it a valuable research topic, this work tries to develop some new facial recognition systems that have both high recognition accuracy and fast running speed. Efforts are made to design facial recognition systems by combining different algorithms. Comparisons...
A face recognition system which represents each image as a superposition of the dominant components in two transform domains is proposed. The Discrete Wavelet Transform (DWT) and the Discrete Cosine Transform (DCT) are the two domains. By the end of the Training mode, each pose in the gallery will have two final matrices. Feature Extraction step in the Training includes transforming the preprocessed...
This work presents security solutions related to multi-sensor closed-loop artificial pancreas (AP) systems. The proposed AP system is built on a heterogeneous platform incorporating a smartphone, activity sensors, a glucose monitor, an insulin pump, a laptop hosting the multi-variable control algorithm and a cloud server. Developing a secure AP system is essential for mass adoption among diabetes...
Command extraction from human beings becomes easier for a machine if it can analyze the non verbal ways of communication such as emotions. This paper focuses on improving the efficiency of extracting emotion from human facial expression images. The features that were extracted in this experiment were obtained from JAFFE (Japanese Female Facial Expression) database which includes 213 images of different...
A new approach based on applying the Two Dimensional Discrete Multiwavelet Transform (2D DMWT) to the partitioned faces is proposed in this paper for face recognition. First, the input facial image is divided into six parts in the preprocessing step to reduce the effect of the unnecessary information (background) on the system performance. Then, the 2D DMWT is applied to each part for feature extraction...
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