Sirindhorn International Institute of Technology

About: Sirindhorn International Institute of Technology is a based out in . It is known for research contribution in the topics: Supply chain & Combustion. The organization has 1048 authors who have published 1678 publications receiving 30067 citations.

Phase Portrait Analysis for Multiresolution Generalized Gradient Vector Flow

Abstract: We propose a modification of the generalized gradient vector flow field techniques based on multiresolution analysis and phase portrait techniques. The original image is subjected to mutliresolutional analysis to create a sequence of approximation and detail images. The approximations are converted into an edge map and subsequently into a gradient field subjected to the generalized gradient vector flow transformation. The procedure removes noise and extends large gradients. At every iteration the algorithm obtains a new, improved vector field being filtered using the phase portrait analysis. The phase portrait is applied to a window with a variable size to find possible boundary points and the noise. As opposed to previous phase portrait techniques based on binary rules our method generates a continuous adjustable score. The score is a function of the eigenvalues of the corresponding linearized system of ordinary differential equations. The salient feature of the method is continuity: when the score is high it is likely to be the noisy part of the image, but when the score is low it is likely to be the boundary of the object. The score is used by a filter applied to the original image. In the neighbourhood of the points with a high score the gray level is smoothed whereas at the boundary points the gray level is increased. Next, a new gradient field is generated and the result is incorporated into the iterative gradient vector flow iterations. This approach combined with multiresolutional analysis leads to robust segmentations with an impressive improvement of the accuracy. Our numerical experiments with synthetic and real medical ultrasound images show that the proposed technique outperforms the conventional gradient vector flow method even when the filters and the multiresolution are applied in the same fashion. Finally, we show that the proposed algorithm allows the initial contour to be much farther from the actual boundary than possible with the conventional methods.

Structural Approach on Writer Independent Nepalese Natural Handwriting Recognition

Abstract: The writing units vary in writer independent un-constrained handwriting (for example, number of strokes, shape, size, order, and speed etc.). Many algorithms were developed to improve the accuracy of the handwriting recognition system in both statistical and structural approaches on real-time databases, from which researchers still are not satisfied. We propose to use structural properties of the feature vector sequences of strokes of variable writing units by using Dynamic Programming (DP). This paper focuses on Dynamic Time Warping (DTW) as a global distance calculation along with the use of local distance metric between two real-time feature vector sequences of strokes and is followed by robust agglomerative hierarchical clustering to produce sensible clusters, which have intrinsic characteristics. We are utilizing feature vector sequences of strokes for both training and testing our recognition system. We work with 20 users and experiment on 36 classes of writer independent real-time Nepalese natural handwritten characters onto our dynamic recognition system stroke by stroke basis and achieve considerable performance.

Autonomous path tracking and disturbance force rejection of UAV using fuzzy based auto-tuning PID controller

Abstract: This paper focuses on the development of a robust, power-efficient control methodology for an unmanned aerial vehicle (UAV) with a quad-rotor mechanism. Two control algorithms are compared and analyzed: a conventional proportional-integral-derivative (PID) controller; and a fuzzy logic-based auto-tuning PID controller. Auto-tuning PID controllers are suited for systems suffering from power constraints, as the algorithm is able to intelligently adjust the gains of the PID controllers so that they maintain robustness and performance while minimizing power consumption for a wide range of external disturbances. The performance results of the two controllers when applied to a quad-rotor UAV are demonstrated using numerical simulations.

An HMM-based method for Thai spelling speech recognition

Abstract: Spelling speech recognition can be applied for several purposes including enhancement of speech recognition systems and implementation of name retrieval systems. This paper presents an approach to construct three recognizers for the three commonly-used Thai spelling methods based on hidden Markov models (HMMs). The Thai phonetic characteristics, alphabet system and spelling methods are analyzed. For the first spelling method, two recognizers, each trained from a small spelling corpus and an existing large continuous speech corpus, are explored. To solve utterance speed difference between spelling utterances and continuous speech utterances, the adjustment of utterance speed is taken into account. Two alternative language models, bigram and trigram, are investigated to evaluate the performance of spelling speech recognition under three different environments: close-type, open-type and mix-type language models. For the first spelling method, our approach achieves up to 93.09% letter correct rate (LCR) and 92.45% letter accuracy (LA) when the language model is trigram under the mix-type environment and the acoustic model is trained from the small spelling corpus. Under the same conditions, we obtained 81.12% LCR and 76.32% LA for the second spelling method and 78.47% LCR and 71.75% LA for the third spelling method. By analyzing the results, it was found that the main source of the errors was letter substitution, which is mostly triggered by the confusion of similar consonant phones and the confusion of short/long vowel pairs.