Flower-like titanium dioxide (TiO2) nanostructures are successfully synthesized using a hybrid sol-gel and a simple hydrothermal method. The sample was characterized using various techniques to study their physicochemical properties and was tested as a photocatalyst for methyl orange degradation and as an antibacterial material. Raman spectrum and X-ray diffraction (XRD) pattern show that the phase structure of the synthesized TiO2 is anatase with 80-100 nm in diameter and 150-200 nm in length of flower-like nanostructures as proved by field emission scanning electron microscope (FESEM). The energy-dispersive X-ray spectroscopy (EDS) analysis of flower-like anatase TiO2 nanostructure found that only titanium and oxygen elements are present in the sample. The anatase phase was confirmed further by a high-resolution transmission electron microscope (HRTEM) and selected area electron diffraction (SAED) pattern analysis. The Brunauer-Emmett-Teller (BET) result shows that the sample had a large surface area (108.24 m2/g) and large band gap energy (3.26 eV) due to their nanosize. X-ray photoelectron spectroscopy (XPS) analysis revealed the formation of Ti4+ and Ti3+ species which could prevent the recombination of the photogenerated electron, thus increased the electron transportation and photocatalytic activity of flower-like anatase TiO2 nanostructure to degrade the methyl orange (83.03%) in a short time (60 minutes). These properties also support the good performance of flower-like titanium dioxide (TiO2) nanostructure as an antibacterial material which is comparable with penicillin which is 13.00 ± 0.02 mm inhibition zone against Staphylococcus aureus.
This is the extended project by introducing the modified dynamic range histogram modification (MDRHM) and is presented in this paper. This technique is used to enhance the scanning electron microscope (SEM) imaging system. By comparing with the conventional histogram modification compensators, this technique utilizes histogram profiling by extending the dynamic range of each tile of an image to the limit of 0-255 range while retains its histogram shape. The proposed technique yields better image compensation compared to conventional methods.
Contrast is a distinctive visual attribute that indicates the quality of an image. Computed Tomography (CT) images are often characterized as poor quality due to their low-contrast nature. Although many innovative ideas have been proposed to overcome this problem, the outcomes, especially in terms of accuracy, visual quality and speed, are falling short and there remains considerable room for improvement. Therefore, an improved version of the single-scale Retinex algorithm is proposed to enhance the contrast while preserving the standard brightness and natural appearance, with low implementation time and without accentuating the noise for CT images. The novelties of the proposed algorithm consist of tuning the standard single-scale Retinex, adding a normalized-ameliorated Sigmoid function and adapting some parameters to improve its enhancement ability. The proposed algorithm is tested with synthetically and naturally degraded low-contrast CT images, and its performance is also verified with contemporary enhancement techniques using two prevalent quality evaluation metrics-SSIM and UIQI. The results obtained from intensive experiments exhibited significant improvement not only in enhancing the contrast but also in increasing the visual quality of the processed images. Finally, the proposed low-complexity algorithm provided satisfactory results with no apparent errors and outperformed all the comparative methods.
An improvement to the previously proposed adaptive Canny optimization technique for scanning electron microscope image colorization is reported. The additional feature, called pseudo-mapping technique, is that the grayscale markings are temporarily mapped to a set of pre-defined pseudo-color map as a mean to instill color information for grayscale colors in chrominance channels. This allows the presence of grayscale markings to be identified; hence optimization colorization of grayscale colors is made possible. This additional feature enhances the flexibility of scanning electron microscope image colorization by providing wider range of possible color enhancement. Furthermore, the nature of this technique also allows users to adjust the luminance intensities of selected region from the original image within certain extent.
A number of techniques have been proposed during the last three decades for noise variance and signal-to-noise ratio (SNR) estimation in digital images. While some methods have shown reliability and accuracy in SNR and noise variance estimations, other methods are dependent on the nature of the images and perform well on a limited number of image types. In this article, we prove the accuracy and the efficiency of the image noise cross-correlation estimation model, vs. other existing estimators, when applied to different types of scanning electron microscope images.
Detection of cracks from stainless steel pipe images is done using contrast stretching technique. The technique is based on an image filter technique through mathematical morphology that can expose the cracks. The cracks are highlighted and noise removal is done efficiently while still retaining the edges. An automated crack detection system with a camera platform has been successfully implemented. We compare crack extraction in terms of quality measures with those of Otsu's threshold technique and the another technique (Iyer and Sinha, 2005). The algorithm shown is able to achieve good results and perform better than these other techniques.
To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts.
This article focuses on the localization of burn mark in MOSFET and the scanning electron microscope (SEM) inspection on the defect location. When a suspect abnormal topography is shown on the die surface, further methods to pin-point the defect location is necessary. Fault localization analysis becomes important because an abnormal spot on the chip surface may and may not have a defect underneath it. The chip surface topography can change due to the catastrophic damage occurred at layers under the chip surface, but it could also be due to inconsistency during metal deposition in the wafer fabrication process. Two localization techniques, liquid crystal thermography and emission microscopy, were performed to confirm that the abnormal topography spot is the actual defect location. The tiny burn mark was surfaced by performing a surface decoration at the defect location using hot hydrochloric acid. SEM imaging, which has the high magnification and three-dimensional capabilities, was used to capture the images of the burn mark.
A new and robust parameter estimation technique, named image noise cross-correlation, is proposed to predict the signal-to-noise ratio (SNR) of scanning electron microscope images. The results of SNR and variance estimation values are tested and compared with nearest neighborhood and first-order interpolation. Overall, the proposed method is best as its estimations for the noise-free peak and SNR are most consistent and accurate to within a certain acceptable degree, compared with the others.
In this paper, we propose to use the autoregressive (AR)-based interpolator with Wiener filter and apply the idea to scanning electron microscope (SEM) images. The concept for combining the AR-based interpolator with Wiener filtering comes from the essential requirement of Wiener filtering for accurate and consistent estimation of the power of the noise in images prior to filter implementation. The resultant filter is called AR-Wiener filter. The proposed filter is embedded onto the frame grabber card of the scanning electron microscope (SEM) for real-time image processing. Different images are captured using SEM and used to compare the performances of the conventional Wiener and the proposed AR-Wiener technique.
A new technique based on the statistical autoregressive (AR) model has recently been developed as a solution to signal-to-noise (SNR) estimation in scanning electron microscope (SEM) images. In the present study, we propose to cascade the Lagrange time delay (LTD) estimator with the AR model. We call this technique the mixed Lagrange time delay estimation autoregressive (MLTDEAR) model. In a few test cases involving different images, this model is found to present an optimum solution for SNR estimation problems under different noise environments. In addition, it requires only a small filter order and has no noticeable estimation bias. The performance of the proposed estimator is compared with three existing methods: simple method, first-order linear interpolator, and AR-based estimator over several images. The efficiency of the MLTDEAR estimator, being more robust with noise, is significantly greater than that of the other three methods.
During the last three decades, several techniques have been proposed for signal-to-noise ratio (SNR) and noise variance estimation in images, with different degrees of success. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image. In this paper, the efficiency of the developed technique with different imaging systems is proven and presented as an optimum solution to image noise variance and SNR estimation problems. Simulation results are carried out with images like Lena, remote sensing, and SEM. The two image parameters, SNR and noise variance, are estimated using different techniques and are compared with the AR-based estimator.
In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor accuracy. In this paper we propose the implementation of autoregressive (AR)-model interpolation as a solution to the problem. Unlike others, the proposed technique is based on a single SEM image and offers the required accuracy and robustness in estimating SNR values.
The preparation and observations of spheroplast W303 cells are described with Environmental Scanning Electron Microscope (ESEM). The spheroplasting conversion was successfully confirmed qualitatively, by the evaluation of the morphological change between the normal W303 cells and the spheroplast W303 cells, and quantitatively, by determining the spheroplast conversion percentage based on the OD800 absorbance data. From the optical microscope observations as expected, the normal cells had an oval shape whereas spheroplast cells resemble a spherical shape. This was also confirmed under four different mediums, that is, yeast peptone-dextrose (YPD), sterile water, sorbitol-EDTA-sodium citrate buffer (SCE), and sorbitol-Tris-Hcl-CaCl2 (CaS). It was also observed that the SCE and CaS mediums had a higher number of spheroplast cells as compared to the YPD and sterile water mediums. The OD800 absorbance data also showed that the whole W303 cells were fully converted to the spheroplast cells after about 15 minutes. The observations of the normal and the spheroplast W303 cells were then performed under an environmental scanning electron microscope (ESEM). The normal cells showed a smooth cell surface whereas the spheroplast cells had a bleb-like surface after the loss of its integrity when removing the cell wall.
White Portland cement (WPC) has generated research interests in the field of endodontics. This study compared between the properties of two formulations of white Portland cement (WPC) of different origin (Malaysia [MA] and Egypt [EG]). WPCs with and without calcium chloride dihydrate were prepared. Scanning electron microscope (SEM), energy dispersive X-ray micro-analysis, and X-ray diffraction were used for surface morphology evaluation, elemental, and phase analysis, respectively. After the preparation of optimized serial dilutions, the cytotoxicity was evaluated on human periodontal ligament fibroblasts (HPLFs) and dental pulp stem cells (DPSCs) using methyl-thiazol-diphenyltetrazolium assay after 24 and 72 h. Cell attachment properties were examined under SEM after 24 and 72 h. Results showed that the surface morphology and chemical composition of both formulations demonstrated detectable variations. The cytotoxicity evaluation showed different cellular responses of HPLFs compared to DSPCs. Both formulations favored the viability of HPLFs. However, the fast set formulations demonstrated severe cytotoxicity on DPSCs. Significant differences between EGWPC and MAWPC were identified (p
The influence of Ta additions on the microstructure and properties of Cu-Al-Ni shape memory alloys was investigated in this paper. The addition of Ta significantly affects the green and porosity densities; the minimum percentage of porosity was observed with the modified prealloyed Cu-Al-Ni-2.0 wt.% Ta. The phase transformation temperatures were shifted towards the highest values after Ta was added. Based on the damping capacity results, the alloy of Cu-Al-Ni-3.0 wt.% Ta has very high internal friction with the maximum equivalent internal friction value twice as high as that of the prealloyed Cu-Al-Ni SMA. Moreover, the prealloyed Cu-Al-Ni SMAs with the addition of 2.0 wt.% Ta exhibited the highest shape recovery ratio in the first cycle (i.e., 100% recovery), and when the number of cycles is increased, this ratio tends to decrease. On the other hand, the modified alloys with 1.0 and 3.0 wt.% Ta implied a linear increment in the shape recovery ratio with increasing number of cycles. Polarization tests in NaCl solution showed that the corrosion resistance of Cu-Al-Ni-Ta SMA improved with escalating Ta concentration as shown by lower corrosion current densities, higher corrosion potential, and formation of stable passive film.