Illumination and Contrast Correction Strategy using Bilateral Filtering and Binarization Comparison

Illumination normalization and contrast variation on images are one of the most challenging tasks in the image processing field. Normally, the degrade contrast images are caused by pose, occlusion, illumination, and luminosity. In this paper, a new contrast and luminosity correction technique is developed based on bilateral filtering and superimpose techniques. Background pixels was used in order to estimate the normalized background using their local mean and standard deviation. An experiment has been conducted on few badly illuminated images and document images which involve illumination and contrast problem. The results were evaluated based on Signal Noise Ratio (SNR) and Misclassification Error (ME). The performance of the proposed method based on SNR and ME was very encouraging. The results also show that the proposed method is more effective in normalizing the illumination and contrast compared to other illumination techniques such as homomorphic filtering, high pass filter and double mean filtering (DMV)

Examining the Trend of Literature on Classification Modelling: A Bibliometric Approach

This paper analyses and reports various types of published works related to classification or discriminant modelling. This paper adopted a bibliometric analysis based on the data obtained from the Scopus online database on 27th July 2019. Based on the ‘keywords’ search results, it yielded 2775 valid documents for further analysis. For data visualisation purposes, we employed VOSviewer. This paper reports the results using standard bibliometric indicators, particularly on the growth rate of publications, research productivity, analysis of the authors and citations. The outcomes revealed that there is an increased growth rate of classification literature over the years since 1968. A total of 2473 (89.12%) documents were from journals (n=1439; 51.86%) and conference proceedings (n=1034; 37.26%) contributed as the top publications in this classification topic. Meanwhile, 2578 (92.9%) documents are multi-authored with an average collaboration index of 3.34 authors per article. However, this classification research field found that the famous numbers of authors’ collaboration in a document are two (with n=758; 27.32%), three (n=752; 27.10%) and four (n=560; 20.18%) respectively. An analysis by country, China with 1146 (41.30%) published documents thus is ranked first in productivity. With respect to the frequency of citations, Bauer and Kohavi (1999)’s article emerged as the most cited article through 1414 total citations with an average of 70.7 citations per year. Overall, the increasing number of works on classification topics indicates a growing awareness of its importance and specific requirements in this research field

Improved wolf algorithm on document images detection using optimum mean technique

Detection text from handwriting in historical documents provides high-level features for the challenging problem of handwriting recognition. Such handwriting often contains noise, faint or incomplete strokes, strokes with gaps, and competing lines when embedded in a table or form, making it unsuitable for local line following algorithms or associated binarization schemes. In this paper, a proposed method based on the optimum threshold value and namely as the Optimum Mean method was presented. Besides, Wolf method unsuccessful in order to detect the thin text in the non-uniform input image. However, the proposed method was suggested to overcome the Wolf method problem by suggesting a maximum threshold value using optimum mean. Based on the calculation, the proposed method obtained a higher F-measure (74.53), PSNR (14.77) and lowest NRM (0.11) compared to the Wolf method. In conclusion, the proposed method successful and effective to solve the wolf problem by producing a high-quality output image

A Comparative Study of Different Blood Vessel Detection on Retinal Images

Detection of blood vessel plays an important stage in different medical areas, such as ophthalmology, oncology, neurosurgery, and laryngology. The significance of the vessel analysis was helped by the continuous overview in clinical studies of new medical technologies intended for improving the visualization of vessels. In this paper, several local segmentation techniques which include such as Vascular Tree Extraction, Tyler L. Coye and Line tracking, Kirsch’s Template and Fuzzy C Mean methods were studied. The main objective is to determine the best approaches in order to detect the blood vessel on the degraded retinal input image (DRIVE dataset). A few Image Quality Assessment (IQA) was obtained to prove the effectiveness of each detection methods. Overall, the result of sensitivity highest came from Kirsch Templates (96.928), while specificity from Fuzzy C means (77.573). However, in term of accuracy average, the Line Tracking method is more successful compared to the other methods

Decision making process in keystroke dynamics

Computer system intrusion often happens nowadays. Various methods have been introduced to reduce and prevent these intrusions, however no method was 100% proven to be effective. Therefore, to improve the computer’s security, this writing will explain the application of KD in the application system. The effectiveness of KD could not guarantee one hundred percent to prevent the computer intrusion, but it can be used as a second level of security after the login page in the application system. The pattern and time taken while typing by an individual is the core for the second level of security check after the login page. This writing will elaborate and conclude past studies related to KD on the aspects of decisionmaking process. Various methods of processing KD data that have been used are listed and the results of the study are compared. The results of this writing are expected to help new researchers in the process of evaluating KD data

Zero-index metamaterial superstrates uwb antenna for microwave imaging detection

Metamaterials (MTM) can enhance the properties of microwaves and also exceed some limitations of devices used in technical practice. Note that the antenna is the element for realizing a microwave imaging (MWI) system since it is where signal transmission and absorption occur. UltraWideband (UWB) antenna superstrates with MTM elements to ensure the signal transmitted from the antenna reaches the tumor and is absorbed by the same antenna. The lack of conventional head imaging techniques, for instance, Magnetic Resonance Imaging (MRI) and Computerized Tomography (CT)scan, has been demonstrated in the paper focusing on the point of failure of these techniques for prompt diagnosis and portable systems. Furthermore, the importance of MWI has been addressed elaborately to portray its effectiveness and aptness for a primary tumor diagnosis. Other than that, MTM element designs have been discussed thoroughly based on their performances towards the contributions to the better image resolution of MWI with detailed reason-ings. This paper proposes the novel design of a Zeroindex Split Ring Resonator (SRR) MTM element superstrate with a UWB antenna implemented in MWI systems for detecting tumor. The novel design of the MTM enables the realization of a high gain of a superstrate UWB antenna with the highest gain of 5.70 dB. Besides that, the MTM imitates the conduct of the zeroreflection phase on the resonance frequency, which does not exist. An antenna with an MTM unit is of a 7 × 4 and 10 × 5 Zero-index SRR MTM element that acts as a superstrate plane to the antenna. Apart from that, Rogers (RT5880) substrate material is employed to fabricate the designed MTM unit cell, with the following characteristics: 0.51 mm thickness, the loss tangent of 0.02, as well as the relative permittivity of 2.2, with Computer Simulation Technology (CST) performing the simulation and design. Both MTM unit cells of 7 × 4 and 10 × 5 attained 0° with respect to the reflection phase at the 2.70 GHz frequency band. The first design, MTM Antenna Design 1, consists of a 7 × 4 MTM unit cell that observed a rise of 5.70 dB with a return loss (S11) −20.007 dB at 2.70 GHz frequency. The second design, MTM Antenna Design 2, consists of 10 × 5 MTM unit cells that recorded a gain of 5.66 dB, having the return loss (S11) −19.734 dB at 2.70 GHz frequency. Comparing these two MTM elements superstrates with the antenna, one can notice that the 7 × 4 MTM element shape has a low number of the unit cell with high gain and is a better choice than the 10 × 5 MTM element in realizing MTM element superstrates antenna for MWI

An Experimental Framework for Assessing Emotions of Stroke Patients using Electroencephalogram (EEG)

Abstract: This research aims to assess the emotional experiences of stroke patients using Electroencephalogram (EEG) signals. Since emotion and health are interrelated, thus it is important to analyse the emotional states of stroke patients for neurofeedback treatment. Moreover, the conventional methods for emotional assessment in stroke patients are based on observational approaches where the results can be fraud easily. The observational-based approaches are conducted by filling up the international standard questionnaires or face to face interview for symptom recognition from psychological reactions of patients and do not involve experimental study. This paper introduces an experimental framework for assessing emotions of the stroke patient. The experimental protocol is designed to induce six emotional states of the stroke patient in the form of video-audio clips. In the experiments, EEG data are collected from 3 groups of subjects, namely the stroke patients with left brain damage (LBD), the stroke patients with right brain damage (RBD), and the normal control (NC). The EEG signals exhibit nonlinear properties, hence the non-linear methods such as the Higher Order Spectra (HOS) could give more information on EEG in the signal’s analysis. Furthermore, the EEG classification works with a large amount of complex data, a simple mathematical concept is almost impossible to classify the EEG signal. From the investigation, the proposed experimental framework able to induce the emotions of stroke patient and could be acquired through EEG

Zero-biasing split ring resonator using metamaterial element for high gain superstrates ultra-wideband antenna

Complex materials with artificial structures known as metamaterials (MTM) have unique properties that draw several scientists to use them in a variety of research fields. In addition, MTM can go beyond some of the restrictions placed on tools used in technical practise while improving the characteristics of microwaves. The Internet of Things (IoT) application calls for the construction of zero-index Split Ring Resonator (SRR) MTM element superstrates with an ultra-wideband antenna. Keep in mind that the MTM simulates behaviour that is not found in nature, namely the zero-reflection phase (dB) on the resonance frequency. For this project, an antenna with an SRR MTM unit cell operating at 2.70 GHz is built. The SRR has four inductance-related loops (r1, r2, r3, and r4), and gaps (slots) are added to the ring to produce the capacitance effect. Parametric research has been done for the SSR in the interim to identify the best design with zero indexes, permittivity and permeability at the desired frequency. The MTM unit cells array design's 7 x 4 and 10 x 5 dimensions achieved a dB of 0° at the 2.70 GHz frequency range. A 7 x 4 MTM unit cell makes up the first design, MTM Antenna Design 1, which at 2.70 GHz recorded a gain of 5.70 dB and a return loss (S11) of-20.007 dB. The return loss (S11) at a frequency of 2.70 GHz was-19.734 dB in the second design, an MTM antenna consisting of 10 x 5 MTM unit cells, which recorded a gain of 5.66 dB

Reviewing and identifying the green criteria in relation to the building cost: project management

To determine the similarities and differences categories of the assessments between the Malaysian green assessment tool for residential building with other countries, six (60 green assessments from six (6)different countries had been chosen; the United State (US) to represent the American region, the United Kingdom (UK)to represent Europe, Japan to represent Asia and Australia. Singapore was chosen as it is very close tot he location of the case study, Malaysia. Each of the countries represents different climate condition except for Singapore and Malaysia which experience the same climate. This paper will show a comparison of each selected green assessment tool under Management/Project Management criterion. The objective is to find out the potential benchmarks which can be applied in developing a cost modal prediction tool for the Malaysian green home