Benchmarking and Comparing Popular Visual SLAM Algorithms

This paper contains the performance analysis and benchmarking of two popular visual SLAM Algorithms: RGBD-SLAM and RTABMap. The dataset used for the analysis is the TUM RGBD Dataset from the Computer Vision Group at TUM. The dataset selected has a large set of image sequences from a Microsoft Kinect RGB-D sensor with highly accurate and time-synchronized ground truth poses from a motion capture system. The test sequences selected depict a variety of problems and camera motions faced by Simultaneous Localization and Mapping (SLAM) algorithms for the purpose of testing the robustness of the algorithms in different situations. The evaluation metrics used for the comparison are Absolute Trajectory Error (ATE) and Relative Pose Error (RPE). The analysis involves comparing the Root Mean Square Error (RMSE) of the two metrics and the processing time for each algorithm. This paper serves as an important aid in the selection of SLAM algorithm for different scenes and camera motions. The analysis helps to realize the limitations of both SLAM methods. This paper also points out some underlying flaws in the used evaluation metrics.Comment: 7 pages, 4 figure

Camera-Captured Document Image Analysis

Text is no longer confined to scanned pages and often appears in camera-based images originating from text on real world objects. Unlike the images from conventional flatbed scanners, which have a controlled acquisition environment, camera-based images pose new challenges such as uneven illumination, blur, poor resolution, perspective distortion and 3D deformations that can severely affect the performance of any optical character recognition (OCR) system. Due to the variations in the imaging condition as well as the target document type, traditional OCR systems, designed for scanned images, cannot be directly applied to camera-captured images and a new level of processing needs to be addressed. In this thesis, we study some of the issues commonly encountered in camera-based image analysis and propose novel methods to overcome them. All the methods make use of color connected components. 1. Connected component descriptor for document image mosaicing Document image analysis often requires mosaicing when it is not possible to capture a large document at a reasonable resolution in a single exposure. Such a document is captured in parts and mosaicing stitches them into a single image. Since connected components (CCs) in a document image can easily be extracted regardless of the image rotation, scale and perspective distortion, we design a robust feature named connected component descriptor that is tailored for mosaicing camera-captured document images. The method involves extraction of a circular measurement region around each CC and its description using the angular radial transform (ART). To ensure geometric consistency during feature matching, the ART coefficients of a CC are augmented with those of its 2 nearest neighbors. Our method addresses two critical issues often encountered in correspondence matching: (i) the stability of features and (ii) robustness against false matches due to multiple instances of many characters in a document image. We illustrate the effectiveness of the proposed method on camera-captured document images exhibiting large variations in viewpoint, illumination and scale. 2. Font and background color independent text binarization The first step in an OCR system, after document acquisition, is binarization, which converts a gray-scale/color image into a two-level image -the foreground text and the background. We propose two methods for binarization of color documents whereby the foreground text is output as black and the background as white regardless of the polarity of foreground-background shades. (a) Hierarchical CC Analysis: The method employs an edge-based connected component approach and automatically determines a threshold for each component. It overcomes several limitations of existing locally-adaptive thresholding techniques. Firstly, it can handle documents with multi-colored texts with different background shades. Secondly, the method is applicable to documents having text of widely varying sizes, usually not handled by local binarization methods. Thirdly, the method automatically computes the threshold for binarization and the logic for inverting the output from the image data and does not require any input parameter. However, the method is sensitive to complex backgrounds since it relies on the edge information to identify CCs. It also uses script-specific characteristics to filter out edge components before binarization and currently works well for Roman script only. (b) Contour-based color clustering (COCOCLUST): To overcome the above limitations, we introduce a novel unsupervised color clustering approach that operates on a ‘small’ representative set of color pixels identified using the contour information. Based on the assumption that every character is of a uniform color, we analyze each color layer individually and identify potential text regions for binarization. Experiments on several complex images having large variations in font, size, color, orientation and script illustrate the robustness of the method. 3. Multi-script and multi-oriented text extraction from scene images Scene text understanding normally involves a pre-processing step of text detection and extraction before subjecting the acquired image for character recognition task. The subsequent recognition task is performed only on the detected text regions so as to mitigate the effect of background complexity. We propose a color-based CC labeling for robust text segmentation from natural scene images. Text CCs are identified using a combination of support vector machine and neural network classifiers trained on a set of low-level features derived from the boundary, stroke and gradient information. We develop a semiautomatic annotation toolkit to generate pixel-accurate groundtruth of 100 scenic images containing text in various layout styles and multiple scripts. The overall precision, recall and f-measure obtained on our dataset are 0.8, 0.86 and 0.83, respectively. The proposed method is also compared with others in the literature using the ICDAR 2003 robust reading competition dataset, which, however, has only horizontal English text. The overall precision, recall and f-measure obtained are 0.63, 0.59 and 0.61 respectively, which is comparable to the best performing methods in the ICDAR 2005 text locating competition. A recent method proposed by Epshtein et al. [1] achieves better results but it cannot handle arbitrarily oriented text. Our method, however, works well for generic scene images having arbitrary text orientations. 4. Alignment of curved text lines Conventional OCR systems perform poorly on document images that contain multi-oriented text lines. We propose a technique that first identifies individual text lines by grouping adjacent CCs based on their proximity and regularity. For each identified text string, a B-spline curve is fitted to the centroids of the constituent characters and normal vectors are computed along the fitted curve. Each character is then individually rotated such that the corresponding normal vector is aligned with the vertical axis. The method has been tested on a data set consisting of 50 images with text laid out in various ways namely along arcs, waves, triangles and a combination of these with linearly skewed text lines. It yields 95.9% recognition accuracy on text strings, where, before alignment, state-of-the-art OCRs fail to recognize any text. The CC-based pre-processing algorithms developed are well-suited for processing camera-captured images. We demonstrate the feasibility of the algorithms on the publicly-available ICDAR 2003 robust reading competition dataset and our own database comprising camera-captured document images that contain multiple scripts and arbitrary text layouts

Data Hiding in Binary Images Using Orthogonal Embedding - A High Capacity Approach

The growth of high speed computer networks and the Internet, in particular, has increased the ease of Information Communication. In comparison with Analog media, Digital media offers several distinct advantages such as high quality, easy editing, high fidelity copying, compression etc. But this type advancement in the field of data communication in other sense has hiked the fear of getting the data snooped at the time of sending it from the sender to the receiver. Information Security is becoming an inseparable part of Data Communication. In order to address this Information Security, Digital Watermarking plays an important role. Watermarking Techniques are used to hide a small amount of data in such a way that no one apart from the sender and intended recipient even realizes there is a hidden message. This paper proposed a high capacity data hiding approach for binary images in morphological transform domain for authentication purpose so that the image will look unchanged to human visual system

QR Code Approach for Examination Process

Using the QR codes is one of the most intriguing ways of digitally connecting consumers to the internet via mobile phones since the mobile phones have become a basic necessity thing of everyone The detection of QR codes, a type of 2D barcode, as described in the literature consists merely in the determination of the boundaries of the symbol region in images obtained with the specific intent of highlighting the symbol .In order to improve the practical application property of the two-dimensional barcode Quick Response (QR) code, we investigate the coding and decoding process of the QR code image. The barcode is a real mechanism for data reads. Data can be stored, embedded and through the scanning device to show. The store of data which being read. In this paper, we present a methodology for creating QR code approach for virtual word examination process by using different techniques like SHA256, encoding, decoding, and Error correction. DOI: 10.17762/ijritcc2321-8169.15024

Effects of Iron Deficiency Anemia and its Treatment on Ghrelins, Obestatin and Heat Shock Protein 70

The impact of iron deficiency anemia (IDA) and its treatment on increased levels of heat shock protein 70 (HSP70) in settings with higher tissue stress induced by both ghrelin, which is both an antioxidant and a food intake stimulant, and also obestatin with opposing effects were investigated. The association of pica with these parameters was also examined. The study included 28 patients with IDA and 28 healthy controls. While acyl ve des-acyl ghrelin values were lower (p<0.05) in IDA. With treatment, ghrelin levels climbed. In IDA, obestatin levels were higher than the control values (p<0.05). With the IDA treatment, acyl and des-acyl Ghrelin levels increased. Contrarily, obestatin values fell down. The concentration of HSP 70 in IDA and during its therapy was above control values. Acyl, des-acyl ghrelin, obestatin, and HSP70 levels were increased in the pica group. In the pica group obestatin/acyl ghrelin ratio was comparatively higher (p<0.05). In IDA decrease in ghrelin and an increase in obestatin levels are observed, while HSP 70 remains the same. An increase in the obestatin/acyl ghrelin ratio might be responsible for the pica disorder

3D printed microwave clamp probe design to detect water level in PVC pipes

This work was supported by Artvin Coruh University Scientific Research Projects Coordinator (BAP). Funding Number is 2019.F14.02.01The permittivity of water is considerably larger than that of air. As the amount of water in PVC water pipes increases, the air will be replaced by water. This means that the electromagnetic environment properties inside the pipe will change. In this study, we proposed a microwave clamp probe designed with a 3D printer that can detect the percentage of water in 50 mm diameter PVC water pipes. The clamp probe allows measurement of return loss from a single port for determining the fill rate of water without any physical intervention from outside the pipe. The clamp, which is structurally similar to a loop antenna, operates at a frequency of 2.45 GHz. As a result of simulations and experimental measurements for different fill percentages of the pipe, the input impedance of the clamp was calculated. Then, an impedance-fill rate graph was created, showing the amount of water in the pipe section according to the impedance values obtained. The impedance seen from the clamp input indicated a linear increase between 40-100 Omega, according to the 0%, 20%, 50%, 80% and 100% of the water in the pipe. The clamp has a compact structure that can be used as a plug-and-play anywhere on the horizontal

Design of an efficiency-enhanced Greinacher rectifier operating in the GSM 1800 band by using rat-race coupler for RF energy harvesting applications

Radio frequency energy harvesting (RFEH) circuits can convert the power of communication signals from radio frequencies (RF) in the environment into direct current and voltage (DC power). In this study, the Greinacher full-wave rectifier circuit topology was combined with a 180 hybrid ring (rat-race) coupler which was a passive RF/microwave circuit. Thus, higher RF-DC conversion efficiency was obtained. First, using the Greinacher rectifier topology, RFEH circuit operating at the center frequency of 1850 MHz was designed. Then, at this frequency, designing of the rat-race coupler having 1000 MHz bandwidth was made. The S-parameter measurements and simulation data of the designed coupler circuit were compared. Finally, the high efficiency rectifier circuit where these two circuits were used together was designed. The proposed rectifier circuit was constructed on 70 × 70 × 1.6 mm3 FR4 substrate material with a permittivity of 4.3 (εr = 4.3). The power conversion efficiency (PCE) of the rectifier circuit, which had 125 MHz bandwidth at the center frequency of 1850 MHz and was developed with rat-race coupler, was calculated as 71% at 4.7 dBm input power. In addition, with this study, at −15 dBm input power, which was a relatively low power level, 40% PCE value was obtained

COVID-19 Pandemisi Sırasında Yetişkin Bireylerde El Hijyen Davranışları: Ne Değişti?

Hand washing is vital to prevent the spread of the agent from person to person during epidemic periods and to reduce the impact of the pandemic on people’s lives, health, livelihoods and health system. Objective: This study was conducted to examine the hand hygiene behavior of adults during the COVID-19 pandemic period. Methods: This descriptive and cross-sectional study was completed between 15 October 2020 and 30 November 2020 via Google Forms with 627 adult individuals. The data were collected with a questionnaire form created by the researchers as a result of the relevant literature review. Results: During the pandemic period, 91.4% of the participants stated that the habit of hand washing increased. It was observed that handwashing status of participants during the pandemic process changed in terms of age group, gender and those who considerg hand hygiene important in combating the epidemic (p<.05). When handwashing behavior of the participants during the COVID-19 pandemic was examined, it was found that only 14.5% of the participants washed their hands before entering a toilet. Nearly all of the participants (96.7%) stated that they wash their hands after using a toilet, 92.7% after coming from outside, 84.1% after shopping, and more than half (52.2%) after meeting with friends or relatives. Conclusions: During the COVID-19 pandemic, awareness of adult individuals about the importance of proper hand hygiene has changed. Handwashing behaviors of individuals in the society change during the pandemic period and this requires the attention of health professionals in particular.El yıkama, salgın dönemlerinde etkenin kişiden kişiye yayılmasını önlemek ve pandeminin bireylerin yaşamı, sağlığı, geçim kaynakları ve sağlık sistemi üzerindeki etkisini azaltmak için hayati önem taşımaktadır. Amaç: Bu çalışma, COVID-19 pandemi döneminde yetişkinlerin el hijyeni davranışlarını incelemek amacıyla yapılmıştır. Yöntem: Tanımlayıcı ve kesitsel tipteki bu araştırma 15 Ekim 2020 - 30 Kasım 2020 arasında Google Forms aracılığıyla 627 yetişkin birey ile tamamlanmıştır. Veriler, ilgili literatür taraması sonucunda araştırmacılar tarafından oluşturulan anket formu ile toplanmıştır. Bulgular: Pandemi döneminde katılımcıların %91.4’ü el yıkama alışkanlığının arttığını belirtmektedir. Katılımcıların pandemi sürecinde el yıkama durumlarının yaş grubu, cinsiyet ve salgınla mücadelede el hijyenine önem verenlere göre değiştiği görülmektedir (p<.05). Katılımcıların COVID-19 pandemisi sırasında el yıkama davranışları incelendiğinde, katılımcıların sadece %14.5’inin tuvalete girmeden önce ellerini yıkadığı tespit edilmiştir. Katılımcıların %96.7’si tuvaleti kullandıktan sonra, %92.7’si dışarıdan geldikten sonra, %84.1’i alışveriş yaptıktan sonra ve yarısından fazlası (%52.2) arkadaş veya akraba ile görüştükten sonra ellerini yıkadığını belirtmiştir. Sonuç: COVID-19 pandemisi sırasında yetişkin bireylerin uygun el hijyeninin önemine ilişkin farkındalıkları değişmiştir. Pandemi döneminde toplumdaki bireylerin el yıkama davranışları değişmekte ve bu durum özellikle sağlık profesyonellerinin dikkatini gerektirmektedir

FORMULATION AND EVALUATION OF LIDOCAINE HYDROCHLORIDE CHEWABLE TABLET

Objective: The objective of this study was to formulate and optimize a chewable formulation of lidocaine hydrochloride using a 32 factorial design for optimized the superdisintegrant concentration.Methods: Various concentrations of sodium starch glycolate (SSG) (13.33 mg, 26.66 mg, and 40 mg) of superdisintegrant and starch (50 mg, 83 mg, and 116.66 mg) were added in the formulation; nine formulations were prepared according to 32 factorial designs and evaluated. The responses were analyzed for analysis of variance using Design-Expert version 10 software. Statistical models were generated for each response parameter. The models were tested for significance. Procedure to manufacture chewable tablets by direct compression was established.Results: The results show that the presence of a superdisintegrant is desirable for chewable formulation. The best-optimized batch F7 found the batch having starch of amount 116.66 mg and SSG 13.33 mg. All the prepared batches of tablets were within the range. Optimized batch F7 showed drug content 102.46±0.0543, wetting time 18±1.7320, friability 0.65±0.0216, and drug release rate 99.97±0.0124% at the end of 30 min.Conclusion: It can be concluded that 32 full factorial design and statistical models can be successfully used to optimize the formulations, and it was concluded that the trial batch F7 is the optimized formulation which compiles official specifications of chewable tablets. The optimized batch was evaluated for thickness, weight variation, hardness, friability, drug dissolution, and stability study for 3 months. The similarity factor was calculated for comparison of dissolution profile before and after stability studies. After 30 min the drug release rate for batch F7 was 98.97% (Table 6). Hence, the results of stability studies reveal that the developed formulation has good stability