Aranya Walairacht

Efficiency Improvement for Unconstrained Face Recognition by Weightening Probability Values of Modular PCA and Wavelet PCA

Principal component analysis (PCA) is a well-known classical appearance-base method in face recognition. In the previous works, the preprocessing process significantly improved the recognition rate. Modular PCA and Wavelet PCA are the preprocessing processes of PCA, which increase the recognition rate of the original PCA. Modular PCA is suitable for the high- varied face database, while Wavelet PCA for the low-varied face database. In this paper, we propose the preprocessing method which combines between Modular PCA and Wavelet PCA with the weightening probability values. The experiments are compared among our propose method, Modular PCA, Wavelet PCA and original PCA with face database from Yale, ORL and UMIST. The experimental results show that the recognition rate of our method is higher compared to the other methods and also support variety of face database.

PCA in wavelet domain for face recognition

In this paper, the preprocessing process aimed to reduce size of input image by using wavelet transform before transformed image is sent to the process of PCA for recognition. We used ORL Face Databases from AT&T Laboratories Cambridge in the experiments. The results show that the 4th Order Symlets level 2 and level 3 improve the accuracy rate of recognition when compare among Haar wavelets, the 4th Order Daubechies wavelets, and biorthogonal wavelets (orthogonal 6.8). In the case of overall processing time for training, the length of filter of wavelet is directly effect the time consuming. Since LL subband of wavelet decomposition becomes the input for PCA, the memory usage can be greatly reduced

Preprocessor to Improve Performance of GA in Determining Bending Process for Sheet Metal Industry

In manufacturing fabricated sheet metal parts, the required shape has to be bent from the flat 2-D layouts. In this bending process, the most complex and critical work is determining the bend sequence and assigning appropriate tools for each bend. Determining the bend sequence is itself a combinatorial problem and this when coupled with tool assignment leads to a huge combination and clearly shows an exhaustive approach is impossible and we propose Genetic Algorithm (GA), an adaptive algorithm to solve the problem. Information regarding the operator knowledge and operator desire are input to the system to generate efficient bending process. And moreover, in order to improve the performance of GA, a preprocessor is being implemented which searches combinable bends and thereby reduce search space and solve the problem in time-economic way.

Adaptive Spai Mail Filtering Using Genetic Algorithm

In this paper, we propose a mechanism for filtering incoming spam mails by generating spam mail prototypes using genetic algorithm. Firstly, words from e-mails are extracted and are categorized by their relating meaning into 7 groups. Then, we compose a string of chromosome having 7 genes, i.e., groups of words. Each gene, represented words in each group, is encoded into binary value. The genetic algorithm and its operations are applied to create varieties of spam mail prototypes which inherit from old spam mails. It saves time for preparing training sets and need no large training set for learning like other methods. The spam mail prototypes are the result of this learning mechanism. The experimental results show that the proposed system has efficiency. When testing with both spams and hams, the accuracy is about 85% in average

Door lock system via web application

This research proposes the smart way to solve the common problem of the conventional door-locking system. The important problems of the ordinary door-locking systems are key lost, forgetting to lock the system and cannot check the lock status from remote. To solve these problems, we proposed a method to lock-unlock the system which utilizes the web application and passcode alongside the usual method of using the ordinary keys. The proposed system can remotely lock, remotely unlock, remotely check door state, remotely check door locking state, send the email to the owner in case of someone knocking on the door and generate the temporary passcode to use in specific date and time.