118 research outputs found
Natural image matting with non-negative matrix factorization
No full textThis report summaries the work done by the author on his Final Year Project at
Nanyang Technological University (NTU) under Associate Professor Deepu Rajan.
The author was involved in implementing an effective way to realize image matting
using Non – Negative Matrix Factorization.
The report provides an overview of the project. It aims to provide the reader an
insight into the author’s role in the development of the matting algorithm. The report
explains the salient features of matting, Non-Negative Matrix Factorization and how
the entire development process was done. The report summarizes the results found
and compares the obtained results with other known algorithms with the use of
images.
It also highlights the domain knowledge, skills gained to accomplish these tasks and
the challenges faced in the process and how they were overcome. The technical
knowledge gained at NTU, was utilized in various ways to fulfill the requirements of
the project.Bachelor of Engineering (Computer Engineering
Microtron Irradiation Induced Tuning of Band Gap and Photoresponse of Al-ZnO Thin Films Synthesized by mSILAR
No full textAl-doped polycrystalline nano ZnO (Al-ZnO) thin films with different doping concentrations were successfully prepared by the microwave-assisted successive ionic layer adsorption and reaction (mSILAR) technique. The structural analysis along with the orientation of the prepared films was examined by powder x-ray diffraction (PXRD) patterns. The deposited film is polycrystalline and the (002) orientation enhanced upon doping. Additional investigations were carried out to study the effect of electron beam irradiation (e−-irradiation) on the band gap and photoconductivity of both irradiated and unirradiated samples. Both the Al doping and e−-irradiation led to the enhancement of the photoconductivity of prepared materials. This property enables us to tune the properties of materials for various applications by controlling dopant concentrations and e−-irradiation. The dependence of photocurrent on e−-irradiation of Al-ZnO thin films was not reported previously. Therefore, Al-doped polycrystalline nano-ZnO thin film is a promising material for band gap engineering and for the development of solar cells
Distinguishing amateur and professional photographs
No full textPhotography is the art of capturing and handling images. There are many ways to define the aesthetics in photography. The act of quantifying these aesthetic properties directly to distinguish photographs taken by amateur and professional photographers is almost impossible. This is because there is no general consensus. As such, it is beneficial to develop an algorithm that can differentiate the photographs.
In today’s technological advanced society, there are several researches done by computer scientist and engineers specialised in the field of image processing to learn aesthetic properties of the photographs. The properties are changed into computable image features for classification of photographs.
The project requires the author to understand and implement one of the research papers. The author furthers his reach by deriving new features he discovered upon learning more about photography. This allowed him to improve on the classification accuracy.
In this report, the author explains the various aesthetic appeals of photographs that are used for photograph classifications. The concept of computer vision and image processing to use to extract these aesthetic properties in order to convert into computable data and the concept of machine learning to train a model which is used to differentiate photographs are studied in order to fulfil this project’s requirement.
To determine the feasibility of the improved design, an application is implemented on MATLAB platform. It automatically takes in thousands of already classified photographs taken by professional and amateur photographer as training datasets and another set of randomly chosen picture as testing datasets. The program, once executed, allows the author to differentiate the photographs. The main features, design methodology and test specification of the application are discussed in this report.
Performances analysis of the implemented application is noted. The author also identified further areas that can be enhanced.Bachelor of Engineering (Computer Engineering
Studies on Evaluation of Suitability of Mango Varieties Sindura, Mallika and Totapuri for Processing into Canned Products and Development of Blended Ready to Serve Beverages
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Direct torque control of three-level inverter fed IPMSM drive
No full textClassical direct torque control (DTC) suffers from problems such as high torque ripples, variable inverter switching frequency and flux drooping at low speeds. Traditionally, two-level inverters are employed in direct torque controlled motor drives. The torque and flux regulation in DTC drives can be improved if three-level inverters are used instead of two-level inverters; the increase in the degree of freedom for voltage vector selection means that the rotational speed of stator flux can be more precisely controlled to attain a superior regulation of torque and flux. At the same time, the broad review presented on the existing three-level inverter fed DTC (3L-DTC) methods at the beginning of this thesis reveal that the integration of three-level inverters into switching table based DTC drives is complicated and does not readily alleviate the shortcomings of classical DTC. Firstly, 3L-DTC drives are typically intended for use in higher power motors and therefore, the average inverter switching frequency has to be kept as low as possible to maximize the drive efficiency. However, if low switching frequencies are used, torque and flux ripples in 3L-DTC schemes can still be excessive and detrimental. Secondly, the inverter inherent switching constraints due to smooth voltage vector switching and neutral point voltage fluctuations, which are essential to reduce low order THD and ensure safe operation, must be respected.
This study focuses on the incorporation of three-level inverters into DTC drives. A number of 3L-DTC strategies incorporating a three-level neutral point clamped (3L-NPC) inverter, one of the most frequently used multilevel inverter in variable speed drives, are proposed and experimentally verified for the control of an interior permanent magnet synchronous motor (IPMSM). The torque variation rates or slopes of permanent magnet synchronous motors are considerably larger than the minimum rate required for the proper regulation of torque during steady state. Consequently, the application of a single voltage vector within one switching period in classical DTC leads to large ripples of torque. Duty cycle based DTC (DDTC) method, in which more than one voltage vectors is applied within each switching cycle, is an effective way to reduce the torque ripples. With the DDTC method, the biggest challenge is to determine the appropriate voltage vectors and their respective duty ratios. The handful of DDTC methods in literature for 3L-DTC drives uses parameter dependent and complicated techniques for duty ratio determination. Furthermore, no consideration is given to the aforementioned inverter switching constraints in selecting the voltage vectors.
In this thesis, a comprehensive analysis is carried out to investigate the typical variation rates of torque and flux in a 3L-DTC IPMSM. Based on this analysis, a novel DDTC method using two voltage vectors, one active and one passive within one switching cycle is proposed. For duty ratio calculation, torque ripple root mean square minimization (TR-RMSM) with minimal parameter dependency is developed, taking into account the dynamics of torque and flux characteristics in an IPMSM. In addition, proper switching techniques are introduced to overcome the problem of smooth voltage vector switching and large neutral point voltage fluctuations.
Ideally for optimal torque ripple reduction, the active and passive voltage vectors applied within each switching cycle in DDTC methods should have opposing variation rates of torque. For instance, the inclusion of a zero voltage vector as a passive vector is necessary for 3L-DTC drives to optimize the torque ripple reduction during medium to low speeds. However, this is not always possible considering the smooth voltage vector switching criteria, which limits the switching transitions to be between adjacent voltage vectors. Therefore, a new DDTC method employing three voltage vectors (one active and two passive) in one switching cycle is proposed in this thesis. The application of three vectors, however, complicates the direct application of TR-RMS method for duty ratio calculations. Consequently, a simplified duty ratio calculation technique which regulates the duty ratio of the non-zero passive vector according to the angular velocity of the motor is developed. Regulating the duty ratio of one passive vector means that aforementioned TR-RMSM method with minimal parameter dependency can be applied.
The low speed performance of 3L-DTC drives is typically affected by poor flux regulation, otherwise known as flux drooping. Flux drooping will increase the lower order harmonics in the output, and thus, affect the efficiency of the drive system. The back emf of the motor is low at low speeds and therefore, voltage vectors with smaller magnitudes are used more frequently. During heavy loads, the significant voltage drop across the stator resistance will cause the stator flux to droop. In order to alleviate the flux drooping issue during low speed, the use of virtual voltage vectors, which are synthesized from two adjacent vectors with smaller magnitudes, are proposed. The proposed method is evaluated through experiments carried out at 3% of the test IPMSMs rated speed. Results confirm that the effects of flux drooping at low speed are mitigated through the use virtual short voltage vectors.
Although the regulation of torque and flux is improved significantly by the proposed DDTC methods, they do not solve the issue of variable inverter switching frequency. The inconsistent variation of torque slope and the usage of fixed torque hysteresis bandwidth are the main causes for variable switching frequency in DTC drives. To attain a constant inverter switching frequency with improved torque and flux regulation, a simple torque regulator, consisting of a PI controller and triangular carriers, is proposed in place of the conventional torque hysteresis controller. The PI controller is used to negate the large variations in torque slope, which is desirable for reducing torque ripples. Then, the output of the PI controller is compared against triangular carriers to attain a constant switching frequency. Detailed analysis and design guidelines for the proposed torque regulator using small signal modeling are presented. In addition, the parametric robustness of the proposed method is experimentally verified.
Almost all of the existing DTC strategies used in multilevel inverter fed DTC (MLI-DTC) drives including the DDTC and constant switching frequency based methods proposed in this thesis are inverter specific. i.e., the level of hysteresis controllers and the proposed switching tables are designed specifically for inverters with a certain number of voltage levels. Therefore, these methods are not readily applicable to generic n-level multilevel inverters. In order to overcome this inconvenience, the proposed CSF strategy is extended to be generalized for inverters possessing any number of voltage levels by using a simple voltage vector decomposition technique. A comparative study with a prior art and parametric sensitivity analysis are presented to verify the effectiveness and robustness of the proposed MLI-DTC method.Doctor of Philosophy (EEE
Brain-computer interface and visual perception
No full textBrain-Computer Interface (BCI) has been a popular area of research, currently we can find several BCI related product in the market. For example the robotic arms that makes use of BCI.
However, BCI should not be just restricted in controlling robotic limbs and machines, but something that is more between humans, like emotions. The question that the author would like to answer in this project is whether our emotion changes when we look at different images. When we look at a happy photo and sad photo, we felt different emotionally. But is there a difference in our brain signal when we see different things? If yes, is it possible to detect and pick up the differences in term of our brain signal?
In this report, the author will be directing a project in developing a BCI system then find out if there exists a difference in EEG signal and later classify the difference into 1 of the 4 different targeted emotions (Anger, Fear, Happy and Sadness). By using a wireless EEG device, EPOC neuroheadset, to retrieve the EEG signal from a person’s scalp. The author also implements a Matlab script to handle the signal processing tasks in order to obtain the EEG signals.
The author also conducts experiments to test out the BCI system, whether it is capable of classifying the emotion of a person when he/she is looking at images of different objects.Bachelor of Engineering (Computer Engineering
Fast Low Frequency Electrochemical Impedance Spectroscopy Measurement, Modeling, and Analysis Techniques
No full textThe rapid advancements in technology today have seen more and more attention placed on the automation of many of our daily life's tasks. This is usually achieved through the use of a variety of sensors and actuators. With both hardware and software being pushed beyond the limits of what we ever thought possible, more focus is now being put on the use of these systems, especially in advancing their rapid measurement ability and in interpreting the data they obtain. Electrochemical Impedance Spectroscopy (EIS) has been regarded as one of the most promising technologies in this field owing to its interesting applications across a wide range of industries. EIS has seen a significant leap particularly in its hardware implementation over the last few years, causing the focus of research to expand toward the utilization of this hardware and the modeling and analysis of measured EIS data. This thesis present various EIS measurement, modeling, and analysis techniques that are meant to contribute to integrating the many EIS applications into the market. This is done by proposing an improved phase extraction technique for a previously proposed magnitude-only impedance measurement technique based on a novel non-uniform Kramers-Kronig transform. Additionally, an extension of the double-dispersion models is presented by combining different single dispersion models. These extended models are validated and proven to give more freedom, improving their fitting accuracy. Moreover, a novel generic model that consists of N sections, each having 3 impedances, is proposed. A machine learning-based circuit model identification technique along with a two-stage optimization routine is also put forward. The technique utilizes the same generic impedance model, with the added value of being able to rapidly model EIS data. Finally, multiple wide band signals for fast low-frequency EIS measurements are presented. The first signal is chaotic, while the second is based on the Rudin-Shapiro polynomial. Both signals were tested with discrete RC circuits and in applications with various fruits and vegetables, while the latter was additionally used to monitor the aging of a strawberry
A Joint QRS Detection and Data Compression Scheme for Wearable Sensors
No full text10.1109/TBME.2014.2342879IEEE Transactions on Biomedical Engineering621165-17
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