Abstract: In this paper a novel method for the detection of
clipping in speech signals is described. It is shown that the new
method has better performance than known clipping detection
methods, is easy to implement, and is robust to changes in signal
amplitude, size of data, etc. Statistical simulation results are
presented.
Abstract: The two primary objectives of this research were (1)
to examine the current knowledge and actual circumstance of
agricultural workers about mangosteen product processing; and (2) to
analyze and evaluate ways to develop capacity of mangosteen
product processing. The population of this study was 15,125 people
who work in the agricultural sector, in this context, mangosteen
production, in the eastern part of Thailand that included Chantaburi
Province, Rayong Province, Trad Province and Pracheenburi
Province. The sample size based on Yamane’s calculation with 95%
reliability was therefore 392 samples. Mixed method was employed
included questionnaire and focus group discussion with
Connoisseurship Model used in order to collect quantitative and
qualitative data. Key informants were used in the focus group
including agricultural business owners, academic people in agro food
processing, local academics, local community development staff,
OTOP subcommittee, and representatives of agro processing
industry professional organizations. The study found that the
majority of the respondents agreed with a high level (in five- rating
scale) towards most of variables of knowledge management in agro
food processing. The result of the current knowledge and actual
circumstance of agricultural human resource in an arena of
mangosteen product processing revealed that mostly, the respondents
agreed at a high level to establish 7 variables. The guideline to
developing the body of knowledge in order to enhance the capacity
of the agricultural workers in mangosteen product processing was
delivered in the focus group discussion. The discussion finally
contributed to an idea to produce manuals for mangosteen product
processing methods, with 4 products chosen: (1) mangosteen soap;
(2) mangosteen juice; (3) mangosteen toffee; and (4) mangosteen
preserves or jam.
Abstract: In this work, a method of time delay estimation for
dual-channel acoustic signals (speech, music, etc.) recorded under
reverberant conditions is investigated. Standard methods based on
cross-correlation of the signals show poor results in cases involving
strong reverberation, large distances between microphones and
asynchronous recordings. Under similar conditions, a method based
on cross-correlation of temporal envelopes of the signals delivers a
delay estimation of acceptable quality. This method and its properties
are described and investigated in detail, including its limits of
applicability. The method’s optimal parameter estimation and a
comparison with other known methods of time delay estimation are
also provided.
Abstract: The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.
Abstract: Any digital processing performed on a signal with larger nyquist interval requires more computation than signal processing performed on smaller nyquist interval. The sampling rate alteration generates the unwanted effects in the system such as spectral aliasing and spectral imaging during signal processing. Multirate-multistage implementation of digital filter can result a significant computational saving than single rate filter designed for sample rate conversion. In this paper, we presented an efficient cascaded integrator comb (CIC) decimation filter that perform fast down sampling using signed digit adder algorithm with compensated frequency droop that arises due to aliasing effect during the decimation process. This proposed compensated CIC decimation filter structure with a hybrid signed digit (HSD) fast adder provide an improved performance in terms of down sampling speed by 65.15% than ripple carry adder (RCA) and reduced area and power by 57.5% and 0.01 % than signed digit (SD) adder algorithms respectively.
Abstract: Based upon generalized analysis of modern know-how in the sphere of processing, concentration and purification of iron-ore raw materials (IORM), in particular, the most widespread ferrioxide-silicate materials (FOSM), containing impurities of phosphorus and other elements compounds, noted special role of nanotechnological initiatives in improvement of such processes. Considered ideas of role of nanoparticles in processes of FOSM carbonization with subsequent direct reduction of ferric oxides contained in them to metal phase, as well as in processes of alkali treatment and separation of powered iron from phosphorus compounds. Using the obtained results the wasteless method of solid-phase processing, concentration and purification of IORM and FOSM from compounds of phosphorus, silicon and other impurities was developed and it excels known methods of direct iron reduction from iron ores and metallurgical slimes.
Abstract: Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronic color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to act as the main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam fixed at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works accurately under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.
Abstract: Background detection is essential in video analyses; optimization is often needed in order to achieve real time calculation. Information gathered by dual cameras placed in the front and rear part of an Autonomous Vehicle (AV) is integrated for background detection. In this paper, real time calculation is achieved on the proposed technique by using Priority Regions (PR) and Parallel Processing together where each frame is divided into regions then and each region process is processed in parallel. PR division depends upon driver view limitations. A background detection system is built on the Temporal Difference (TD) and Gaussian Filtering (GF). Temporal Difference and Gaussian Filtering with multi threshold and sigma (weight) value are be based on PR characteristics. The experiment result is prepared on real scene. Comparison of the speed and accuracy with traditional background detection techniques, the effectiveness of PR and parallel processing are also discussed in this paper.
Abstract: In this paper, a simple moving human detection method is proposed for video surveillance system or access monitoring system. The frame difference and noise threshold are used for initial detection of a moving human-object, and simple labeling method is applied for final human-object segmentation. The simulated results show that the applied algorithm is fast to detect the moving human-objects by performing 95% of correct detection rate. The proposed algorithm has confirmed that can be used as an intelligent video access monitoring system.
Abstract: The mixing of two or more liquids is very common in many industrial applications from automotive to food processing. CFD simulations of these processes require comparison with test results. In many cases it is practically impossible. Therefore, comparison provides with scalable tests. So, parameterization of the problem is sufficient to capture the performance of the mixer.
However, the influence of geometrical and thermo-physical parameters on the mixing is not well understood.
In this work influence of geometrical and thermal parameters was studied. It was shown that for full developed turbulent flows (Re > 104), Pet»const and concentration of secondary fluid ~ F(r/l).
In other words, the mixing is practically independent of total flow rate and scale for a given geometry and ratio of flow rates of mixing flows. This statement was proved in present work for different geometries and mixtures such as EGR and water-urea mixture.
Present study has been shown that the best way to improve the mixing is to establish geometry with the lowest Pet number possible by intensifying the turbulence in the domain. This is achievable by using step geometry, impinging flow EGR on a wall, or EGR jets, with a strong change in the flow direction, or using swirler like flow in the domain or combination all of these factors. All of these results are applicable to any mixtures of no compressible fluids.
Abstract: In this paper we introduce an effective ECG compression algorithm based on two dimensional multiwavelet transform. Multiwavelets offer simultaneous orthogonality, symmetry and short support, which is not possible with scalar two-channel wavelet systems. These features are known to be important in signal processing. Thus multiwavelet offers the possibility of superior performance for image processing applications. The SPIHT algorithm has achieved notable success in still image coding. We suggested applying SPIHT algorithm to 2-D multiwavelet transform of2-D arranged ECG signals. Experiments on selected records of ECG from MIT-BIH arrhythmia database revealed that the proposed algorithm is significantly more efficient in comparison with previously proposed ECG compression schemes.
Abstract: Image Edge Detection is one of the most important
parts of image processing. In this paper, by fuzzy technique, a new
method is used to improve digital image edge detection. In this
method, a 3x3 mask is employed to process each pixel by means of
vicinity. Each pixel is considered a fuzzy input and by examining
fuzzy rules in its vicinity, the edge pixel is specified and by utilizing
calculation algorithms in image processing, edges are displayed more
clearly. This method shows significant improvement compared to
different edge detection methods (e.g. Sobel, Canny).
Abstract: In this paper, we validate crater detection in moon surface image using FLDA. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) project aiming at the pin-point landing to the moon surface. The point where the lander should land is judged by the position relations of the craters obtained via camera, so the real-time image processing becomes important element. Besides, in the SLIM project, 400kg-class lander is assumed, therefore, high-performance computers for image processing cannot be equipped. We are studying various crater detection methods such as Haar-Like features, LBP, and PCA. And we think these methods are appropriate to the project, however, to identify the unlearned images obtained by actual is insufficient. In this paper, we examine the crater detection using FLDA, and compare with the conventional methods.
Abstract: In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
Abstract: The increase popularity of multimedia application especially in image processing places a great demand on efficient data storage and transmission techniques. Network communication such as wireless network can easily be intercepted and cause of confidential information leaked. Unfortunately, conventional compression and encryption methods are too slow; it is impossible to carry out real time secure image processing. In this research, Embedded Zerotree Wavelet (EZW) encoder which specially designs for wavelet compression is examined. With this algorithm, three methods are proposed to reduce the processing time, space and security protection that will be secured enough to protect the data.
Abstract: This paper describes a rapid prototyping (RP)
technology for forming a hydroxyapatite (HA) bone scaffold model.
The HA powder and a silica sol are mixed into bioceramic slurry form
under a suitable viscosity. The HA particles are embedded in the
solidified silica matrix to form green parts via a wide range of process
parameters after processing by selective laser sintering (SLS). The
results indicate that the proposed process was possible to fabricate
multilayers and hollow shell structure with brittle property but
sufficient integrity for handling prior to post-processing. The
fabricated bone scaffold models had a surface finish of 25
Abstract: The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.
Abstract: Most of the Question Answering systems
composed of three main modules: question processing,
document processing and answer processing. Question
processing module plays an important role in QA systems. If
this module doesn't work properly, it will make problems for
other sections. Moreover answer processing module is an
emerging topic in Question Answering, where these systems
are often required to rank and validate candidate answers.
These techniques aiming at finding short and precise answers
are often based on the semantic classification.
This paper discussed about a new model for question
answering which improved two main modules, question
processing and answer processing.
There are two important components which are the bases
of the question processing. First component is question
classification that specifies types of question and answer.
Second one is reformulation which converts the user's
question into an understandable question by QA system in a
specific domain. Answer processing module, consists of
candidate answer filtering, candidate answer ordering
components and also it has a validation section for interacting
with user. This module makes it more suitable to find exact
answer. In this paper we have described question and answer
processing modules with modeling, implementing and
evaluating the system. System implemented in two versions.
Results show that 'Version No.1' gave correct answer to 70%
of questions (30 correct answers to 50 asked questions) and
'version No.2' gave correct answers to 94% of questions (47
correct answers to 50 asked questions).
Abstract: Wireless sensor network can be applied to both abominable
and military environments. A primary goal in the design of
wireless sensor networks is lifetime maximization, constrained by
the energy capacity of batteries. One well-known method to reduce
energy consumption in such networks is data aggregation. Providing
efcient data aggregation while preserving data privacy is a challenging
problem in wireless sensor networks research. In this paper,
we present privacy-preserving data aggregation scheme for additive
aggregation functions. The Cluster-based Private Data Aggregation
(CPDA)leverages clustering protocol and algebraic properties of
polynomials. It has the advantage of incurring less communication
overhead. The goal of our work is to bridge the gap between
collaborative data collection by wireless sensor networks and data
privacy. We present simulation results of our schemes and compare
their performance to a typical data aggregation scheme TAG, where
no data privacy protection is provided. Results show the efficacy and
efficiency of our schemes.
Abstract: Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.