896 resultados para Hand posture recognition


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n this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results.

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Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.

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This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

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Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification

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In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvature direction is used as the curvature feature. The proposed system uses a combination of gradient and curvature feature in reduced dimension as the feature vector. For classification, discriminative power of Support Vector Machine (SVM) is evaluated. The results reveal that SVM with Radial Basis Function (RBF) kernel yield the best performance with 96.28% and 97.96% of accuracy in two different datasets. This is the highest accuracy ever reported on these datasets

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Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.

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Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam isolated speech recognizer based on PLP (Perceptual Linear Predictive) Cepstral Coefficient and Hidden Markov Model (HMM). The performance of the developed system has been evaluated with different number of states of HMM (Hidden Markov Model). The system is trained with 21 male and female speakers in the age group ranging from 19 to 41 years. The system obtained an accuracy of 99.5% with the unseen data

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A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.

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A primary medium for the human beings to communicate through language is Speech. Automatic Speech Recognition is wide spread today. Recognizing single digits is vital to a number of applications such as voice dialling of telephone numbers, automatic data entry, credit card entry, PIN (personal identification number) entry, entry of access codes for transactions, etc. In this paper we present a comparative study of SVM (Support Vector Machine) and HMM (Hidden Markov Model) to recognize and identify the digits used in Malayalam speech.

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This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds

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Control of protein synthesis is a key step in the regulation of gene expression during apoptosis and the heat shock response. Under such conditions, cap-dependent translation is impaired and Internal Ribosome Entry Site (IRES)-dependent translation plays a major role in mammalian cells. Although the role of IRES-dependent translation during apoptosis has been mainly studied in mammals, its role in the translation of Drosophila apoptotic genes has not been yet studied. The observation that the Drosophila mutant embryos for the cap-binding protein, the eukaryotic initiation factor eIF4E, exhibits increased apoptosis in correlation with up-regulated proapoptotic gene reaper (rpr) transcription constitutes the first evidence for the existence of a cap-independent mechanism for the translation of Drosophila proapoptotic genes. The mechanism of translation of rpr and other proapoptotic genes was investigated in this work. We found that the 5 UTR of rpr mRNA drives translation in an IRES-dependent manner. It promotes the translation of reporter RNAs in vitro either in the absence of cap, in the presence of cap competitors, or in extracts derived from heat shocked and eIF4E mutant embryos and in vivo in cells transfected with reporters bearing a non functional cap structure, indicating that cap recognition is not required in rpr mRNA for translation. We also show that rpr mRNA 5 UTR exhibits a high degree of similarity with that of Drosophila heat shock protein 70 mRNA (hsp70), an antagonist of apoptosis, and that both are able to conduct IRES-mediated translation. The proapoptotic genes head involution defective (hid) and grim, but not sickle, also display IRES activity. Studies of mRNA association to polysomes in embryos indicate that both rpr, hsp70, hid and grim endogenous mRNAs are recruited to polysomes in embryos in which apoptosis or thermal stress was induced. We conclude that hsp70 and, on the other hand, rpr, hid and grim which are antagonizing factors during apoptosis, use a similar mechanism for protein synthesis. The outcome for the cell would thus depend on which protein is translated under a given stress condition. Factors involved in the differential translation driven by these IRES could play an important role. For this purpose, we undertook the identification of the ribonucleoprotein (RNP) complexes assembled onto the 5 UTR of rpr mRNA. We established a tobramycin-affinity-selection protocol that allows the purification of specific RNP that can be further analyzed by mass spectrometry. Several RNA binding proteins were identified as part of the rpr 5 UTR RNP complex, some of which have been related to IRES activity. The involvement of one of them, the La antigen, in the translation of rpr mRNA, was established by RNA-crosslinking experiments using recombinant protein and rpr 5 UTR and by the analysis of the translation efficiency of reporter mRNAs in Drosophila cells after knock down of the endogenous La by RNAi experiments. Several uncharacterized proteins were also identified, suggesting that they might play a role during translation, during the assembly of the translational machinery or in the priming of the mRNA before ribosome recognition. Our data provide evidence for the involvement of La antigen in the translation of rpr mRNA and set a protocol for purification of tagged-RNA-protein complexes from cytoplasmic extracts. To further understand the mechanisms of translation initiation in Drosophila, we analyzed the role of eIF4B on cap-dependent and cap-independent translation. We showed that eIF4B is mostly involved in cap-, but not IRES-dependent translation as it happens in mammals.

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Gefördert vom Beauftragten der Bundesregierung für Kultur und Medien aufgrund eines Beschlusses des Deutschen bundestages sowie mit freundlicher Unterstützung der Vereinigten Kurländischen Stiftungen

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Die vorliegende Arbeit beschäftigt sich mit der Besteuerung der öffentlichen Hand an Personenhandelsgesellschaften. Hierbei wird der Frage nach der steuerrechtlichen Beurteilung einer solchen nachgegangen. Es wird hinterfragt, ob die in der Rechtsprechung, Verwaltungsanweisungen und Richtlinien der Finanzverwaltung sowie der Literatur vertretenen Auffassungen haltbar sind oder ob diese revidiert werden müssen. Hierzu werden im ersten Teil der Arbeit die theoretischen Grundlagen der sowohl rechtlichen als auch ökonomischen Problemfelder erarbeitet. Auf dieser Grundlage werden die Sichtweise der Rechtsprechung, Verwaltungsvorschriften und Richtlinien der Finanzverwaltung sowie der einschlägigen Literatur kritisch evaluiert und im Hinblick auf Unstimmigkeiten und sich daran anschließenden Gestaltungsbedarf untersucht. Im zweiten der Teil der Arbeit werden die im ersten Teil gefundenen Ergebnisse und Erkenntnisse anhand von ausgewählten Fällen diskutiert und aus diesen ökonomische und rechtlich abgesicherte Gestaltungsoptionen abgeleitet. Im dritten Teil der Arbeit werden die Kernaussagen zusammengefasst und die zentralen Ergebnisse aufgelistet. Im Abschließenden Ausblick werden die Mängel des Jahresteuergesetzes 2009 in Bezug auf die Personenhandelsgesellschaften an denen die öffentliche Hand beteiligt ist im Hinblick auf die steuerlichen Regelungen in Verbindung mit dem Anwendnungserlass des BMF gerügt.