Text Font Research Articles

AUTOMATIC NUMBER PLATE RECOGNITION FOR DIFFERENT FONTS AND NON-ROMAN SCRIPT

According to survey taken the total number of vehicles in [1] India were 260 million. Therefore, there is a need to develop Automatic Number Plate Recognition (ANPR) systems [1] in India because of the large number of vehicles travelling on the roads. [1] It would also help in proper tracking of the vehicles, traffic examining, finding stolen vehicles, supervising parking toll and imposing strict actions against red light breaching. Automatic number plate recognition is image processing technique for finding number plate from image and extracting characters from detected number plate. ANPR in India has always been challenging due to different lighting conditions, changes in fonts, shapes, angles, letters size, number of lines and padding between lines, different languages used. In our project we proposed a model that can detects number plate with considering all irregularities. this system uses Computer vision and machine learning technology in order to detect number plate from image. In our proposed system number plate can be of different fonts and non-roman script. For identification of characters from number plate we use OCR (Optical character recognition) technique. OCR involves two parts: Character segmentation and Character Recognition. This OCR system can be used to extract characters of different fonts and non-roman script. The Quality of OCR depends on the quality of image, image contrast, text font style and size. To improve quality of OCR we can use image processing technique to enhance quality of image.

The effect of signaling in dependence on the extraneous cognitive load in learning environments

Text-based learning media are often used in primary, secondary and university education. Therefore, text designers can support the learner by highlighting the most relevant information by using visual cues. Despite this signaling effect’s broad empirical basis, the extent to which the effectiveness of educational signals is dependent on moderator variables, like the design and layout of the text has not been investigated to date. In the current experiment, 138 university students learned about the formation of tsunamis from an instructional text. The text was manipulated in terms of signaling (color cues vs. no color cues) and induced learning-irrelevant extraneous cognitive load (fluent text font vs. disfluent text font). The results revealed that learners who had received the signaled text outperformed those who received the non-signaled text in terms of transfer performance. These results are explained by cognitive load, which was reduced in the signaling condition. The text font had no influence on the learning outcomes. Extraneous load induction further led to higher metacognitive accuracy and invested effort, while cognitive load and frustration were also increased. Interaction effects only occurred in terms of testing time, ease of learning and navigation. Results indicate that signaling is beneficial for transfer performance, independent of the font design of text.

Individual Differences in Font Preference & Effectiveness as Applied to Interlude Reading in the Digital Age

In the age of pervasive reading on digital devices, incredible opportunities for customized interfaces abound. We consider how personalizing body text font can improve reading outcomes for adult readers. We present results of large-scale Interlude Reading experiments run on 386 crowdsourced participants, whereby we tested 16 body text fonts and measured impacts on font preference and reading speed. We define “Interlude Reading,” nestled between glanceable and long-form reading, as the form of reading that occurs in short interludes and is common in the mobile context. Our studies controlled for participants’ interest and familiarity with reading passages, familiarity with font families, and font size - via a perceptually-based font size normalization technique. While past work has considered how these factors affect reading in isolation, we present the first study that combines these factors under a single experimental methodology. First, our results show that normalizing a font’s size affects reading speed and font preferences. Second, familiarity with a font predicts neither preference nor effectiveness of a font. Third, people do not know what is good for them: despite 80% of people believing their most preferred font would be their most effective for reading, this was only true 18% of the time. Fourth, and most surprisingly, a simple change in font yielded a reading speed gain of 38 words per minute on average, and 93 WPM for our top quartile of participants (equivalent to eight pages an hour) while comprehension remained similarly high. With these results, we put forward (1) a methodology for running large-scale controlled reading studies, (2) a computational toolkit of crowdsourcing experiments, and (3) a list of concrete recommendations about favorable and effective fonts, and font normalization strategies. Moreover, the potential impacts on individual reading efficacy highlighted here demonstrate a need to further exploit the personalization of text formats.

The Visual made Audible – Co-constructing Sound Effects as Devices of Comic Book Literacy in Primary School

This paper analyses and discusses ongoing comics literacy events where two 3rd Grade students and their teachers are working with comic books, focusing specifically on visual representations of sound. The purpose of the paper is to explore how these representations, as multimodal aspects of comics literacy, provoke literacy experiences in the classroom. Visual representations of sound come in different shapes and sizes, but are generally written outside of speech bubbles in bold letters. Using discursive psychology –allowing the researcher to view participants’ verbal and embodied actions as performing actions in social and situated contexts– the current paper analyses how pairs of students and teachers co-construct visual aspects in comic books, translating them into verbal sound and embodied action. Results show that embodied motion, sensation, and audible sound are utilized to interactively display comic sound effects to enhance the reader’s experience of the narrative. This is done as co-construction between adult and child through re-enactment of the visuals as real-life sound and action –also connecting this to other visual aspects of adjacent panels in order to make this meaningful. The paper argues that this challenges both teachers’ and students’ perceptions of what literacy can be and how sound effects –through the shape, colour and font of the graphic text– influence and enliven the comic narratives created in the classroom.

Focus group testing of a mobile app for pharmacogenetic-guided dosing.

A common barrier to implementation of precision medicine is the lack of use of published clinical practice guidelines. Consequently, a user-friendly mechanism to easily adopt these guidelines is imperative. The purpose of this study was to evaluate the perceptions of a prototype of a clinical decision support tool through a mobile application for pharmacogenetics. A case study on a patient requiring pharmacogenetic testing was provided to the participants. The participants were given up to 30 minutes to identify the correct dosing in the clinical decision support tool based on clinical evidence-based guidelines. Immediately after the utilization of the mobile app, focus group interviews were conducted to identify the perceptions of the tool, obstacles associated with the tool, and suggestions for improvement of the tool. Focus group interviews with 23 nurse practitioners and nurse practitioner students were conducted. Field notes and audio recordings were taken. Specific feedback for improvement in the font and size of text, color contrast, use of drug calculator, automatic input, and desire for further development of education portal were found within the data. The findings revealed useful feedback to adjust the prototype to improve the ease of use among nurse practitioners. The revision of this mobile app will improve user friendliness to increase applicability within health care. The mobile app can be used for future research to identify improvements in patient outcomes after implementing this tool.

Arbitrarily Shaped Scene Text Detection with a Mask Tightness Text Detector.

Scene text in the environment is complicated. It can exist in arbitrary text fonts, sizes or shapes. Although scene text detection has witnessed considerable progress in recent years, the detection of text with complex shapes, especially curved text, remains challenging. Datasets with adequate samples to overcome the problem presented by curved text (or other irregularly shaped text) have been introduced only recently; however, the performance of the reported methods on these datasets is unsatisfactory. Therefore, detecting arbitrarily shaped text remains a challenging. This motivated us to propose the Mask Tightness Text Detector (Mask TTD) to improve text detection performance. Mask TTD uses a tightness prior and text frontier learning to enhance pixel-wise mask prediction. In addition, it achieves mutual promotion by integrating a branch for the polygonal boundary of each text region, which significantly improves the detection performance of arbitrarily shaped text. Experiments demonstrate that Mask TTD can achieve state-ofthe-art performance on existing curved text datasets (CTW1500, Total-text, and CUTE80) and three common benchmark datasets (RCTW-17, MSRA-TD500, and ICDAR 2015). It is worth mentioning that on CTW1500, our method can outperform previous methods, especially at higher intersection over union (IoU) thresholds (16% higher than the next-best method with an IoU threshold of 0.8), which demonstrates its potential for tight text detection. Moreover, on the largest Chinese-based dataset RCTW-17, Mask TTD outperforms other methods by a large margin in terms of both the Average Precision and F-measure, showing its powerful generalization ability.

An algorithm to identify text marked in rock core pictures with machine learning algorithm

The aim of our project is to extract numerical descriptors or gather feature of rock samples from their images made under microscope with computer vision algorithm which can overcome the bottleneck of traditional method. It is impossible to solve it without getting the imformation of microscope magnification of images when they were made. That is why this paper is about an algorithm to identify the text used to mark microscope magnification information in rock core sample pictures. This is a sub project. As locations of text in these pictures are not fixed, font of text is not fixed, font size of text is not fixed, a method of two steps is designed to identify the text from the background. It works as follows: first, find the location of text; second, recognize the text with Convolution Neural Network. Experimental results demonstrate the potential value of the proposed approach to identify the magnification information in rock core sample pictures and to apply as a funtion to a program of our future project.

Natural scene text localization using edge color signature

Localizing text regions in images taken from natural scenes is one of the challenging problems dueto variations in font, size, color and orientation of text. In this paper, we introduce a new concept socalled Edge Color Signature for localizing text regions in an image. This method is able to localizeboth Farsi and English texts. In the proposed method rst a pyramid using different scales of theinput image is created. Then for each level of the pyramid an edge map is extracted. Afterward,several geometric features are employed to lter out the non-text edges from the extracted edges.At this stage we describe an edge using colors of its neighboring pixels. We use the mean-Shiftalgorithm to obtain the color modes surrounding each edge pixel. Subsequently, the connectededge pixels with similar color signatures are clustered using Single-Linkage clustering algorithm toconstruct meaningful groups. Finally, each of the clusters is labeled as text or non-text using anMLP based cascade classi er. The proposed method has been evaluated on well-known ICDAR 2013and our Farsi dataset, the result is very promising.

The Influence of the Interface Button Design of Touch Screens on Operation and Interpretation by Elderly and Middle-Aged Adults

Body function begins to decline in middle age, with changes becoming increasingly noticeable over time. With the popularization of educational and information technology, people know more about healthcare and are becoming accustomed to self-testing using health equipment. Technological changes are reflected in products, which present innovations including the switch from traditional to touch-controlled interface designs. This can cause difficulties in the interpretation and interface operation for older adults, who may be facing physiological and psychological alterations. Understanding users’ physiological limitations has become an important aspect of product design. This study explored the effects of physiological limitations on touch-screen operation in middle-aged and elderly people, specifically regarding button type, display position, and button size. A total of 64 participants were included in the study: 32 middle-aged people (aged 45–64 years) and 32 elderly people (65 years of age and older). Each participant was asked to complete 32 tasks (two button categories × four button sizes × four presentation positions). The results revealed no differences between the elderly and the middle-aged groups with regard to the interpretation of image buttons and text buttons; however, button size affected the operation and interpretation time. Middle-aged participants demonstrated good interpretation performance when the buttons were displayed in the upper or lower part of the screen, whereas elderly participants only had a good interpretation performance when the buttons were in the upper part. For both groups, the ideal image button size was 16 mm with a text font size of 22.

Implementation Challenges in Information Retrieval System

Natural scenes text recognition has become increasingly attractive in recent years. Several research results have been developed on different languages for the sake of text recognition from natural scenes. However, there is no system for identifying Urdu text from natural scenes. This paper presents a framework steps involved in recognition of Urdu text from landscape images. Furthermore, the paper focus on issues and challenges faced during experimentation and implementation. Challenges includes multi-script text on a single image, different text font with variation in text sizes, light shadow, reflection, text color, text contrast with background, words or ligature missing, blur, low resolution , skew and neon signboard. In the end, we also give a summary of issues and challenges of Urdu Text retrieval system from natural scenes.

How to Code a Sandcastle by J. Funk

Funk, Josh. How to Code a Sandcastle. Illustrated by Sara Palacios, Viking, 2018.
 How to Code a Sandcastle, written by Josh Funk, is endorsed as a “Girls Who Code” book. Founded in 2013, the mission of Girls Who Code is to close the gender gap in technology. One of the tools they use to help them reach their young female target audience is children’s literature. The story begins with the protagonist, Pearl, comically explaining a variety of challenges she encountered when building a sandcastle at the beach. Now, on the last day of her summer vacation, Pearl has decided to recruit the help of her robot, Pascal, to build her sandcastle. Pearl gives instructions to Pascal, using code, and explains the coding concepts of sequence, loop, and if-then-else to the reader as they relate to the task of building her sandcastle. These concepts are introduced and explained to the young readers in a fun and engaging manner.
 The text features of this book are eye catching and educational. Josh Funk strategically changes the text color to highlight coding vocabulary and he draws the reader’s attention to coding commands by changing the text font when Pearl is giving instructions to Pascal. Speech bubbles are used throughout the book in an appealing, non-linear manner. The illustrations are interesting, colourful, and visually captivating to all readers, young and old. The images are crafted with purpose as they enhance the reader’s ability to make meaning of the coding concepts by providing them with visual information to complement and reinforce the descriptions given in the text. The last two pages of the book, Pearl and Pascal’s Guide to Coding, give a more in-depth explanation of the coding concepts, providing extra support for children and adults who may be new to coding. This book is an entertaining and educational must read!
 Highly Recommended: 4 stars out of 4Reviewer: Dannielle Sehgal
 Dannielle Sehgal is a kindergarten teacher and graduate student at the University of Alberta. Dannielle is passionate about her career and loves discovering new picture books that she can bring to her classroom and read to her students.

The Current Status of Accessibility in Mobile Apps

This study evaluated the status of accessibility in mobile apps by investigating the graphical user interface (GUI) structures and conformance to accessibility guidelines of 479 Android apps in 23 business categories from Google Play. An automated tool, IBM Mobile Accessibility Checker (MAC), was used to identify the accessibility issues, which were categorized as a violation (V), potential violation (PV), or warning (W). The results showed 94.8%, 97.5%, and 66.4% of apps studied contained issues related to V, PV, or W, respectively. Five widget categories (TextView, ImageView, View, Button, and ImageButton) were used to create 92% of the total number of the GUI elements and caused 89%, 78%, and 86% of V, PV, and W, respectively. These accessibility issues were mainly caused by lack of element focus, missing element description, low text color contrast, lack of sufficient spacing between elements, and less than minimum sizes of text fonts and elements. Together, these accessibility issues accounted for 97.0%, 77.8%, and 94.5% of V, PV, and W, respectively. This study proposed coverage measures to estimate the percentage of accessibility issues identified by an automated tool. The result showed that MAC, on average, identified about 67% of accessibility issues in mobile apps. Two new accessibility conformance measures were proposed in this study: inaccessible element rate (IAER) and accessibility issue rate (AIR). IAER estimates the percentage of GUI elements that are inaccessible. AIR calculates the percentage of the actual number of accessibility issues relative to the maximum number of accessibility issues. Average IAER and AIR scores were 27.3%, 19.9%, 6.3% and 20.7%, 15.0%, 5.4% for V, PV, and W, respectively, for the studied apps. The IAER score showed approximately 30% of the GUI elements had accessibility issues, and the AIR score indicated that 15% of the accessibility issues remained and need to be fixed to make the apps accessible.

Legibility of Light-Emitting Diode Destination Indicators Mounted on the Front of Public Buses

Light-emitting diode (LED) destination indicators mounted on the front of buses enable pedestrians to quickly identify bus numbers. In this study, the factors affecting their legibility were investigated. We aimed to deduce the process of enhancing the legibility of LED destination indicators. Combinations of different text colors, text fonts and information display locations were investigated in this study. Significant differences were observed at the longest visual range when these combinations were used. The optimal information display was obtained using the New Johnston Medium typeface with yellow font color on a black background. For the glare distance, significant differences were observed when different information display locations were used. Superior results were obtained when information was centered. This study is of practical importance to people who depend on public transport, especially those in an emergency. In the future, these results can be used as a guide for designing LED destination indicators that are mounted on the front of public buses.

Digital version of the Rapid Automatized Naming (RAN): a contribution to early detection of reading problems in children

ABSTRACT Purpose: to present a digital version of the Rapid Automatized Naming (RAN) test, designed to be used as an auxiliary tool for early detection of reading problems in children. Methods: the application was designed to provide resources, such as: a) registration; b) information security with the online authentication system - individuals are only seen by the person who registered them and, c) history of the results. In order to know the impressions of speech therapists and professionals of children’s education area about this digital version of RAN test, a public opinion survey was conducted with unidentified participants by Google Forms. Results: the application has an automatic speech recognition and allows registering and accessing the history of the application, including statistical evaluation of the results. The application features a responsive interface that adapts to the dimensions of the mobile device with soft colors, and offers a variety of text font options. The images of the objects of the digital version were elaborated by a designer. Conclusion: the application presents itself as a useful digital tool that assists professionals to evaluate, early, children with reading difficulties, highlighting the following elements: exclusive and appropriate images to children’s universe and the function of storing the results of users tested.

Optimizing Whole-Page Presentation for Web Search

Modern search engines aggregate results from different verticals : webpages, news, images, video, shopping, knowledge cards, local maps, and so on. Unlike “ten blue links,” these search results are heterogeneous in nature and not even arranged in a list on the page. This revolution directly challenges the conventional “ranked list” formulation in ad hoc search. Therefore, finding proper presentation for a gallery of heterogeneous results is critical for modern search engines. We propose a novel framework that learns the optimal page presentation to render heterogeneous results onto search result page (SERP). Page presentation is broadly defined as the strategy to present a set of items on SERP, much more expressive than a ranked list. It can specify item positions, image sizes, text fonts, and any other styles as long as variations are within business and design constraints. The learned presentation is content aware, i.e., tailored to specific queries and returned results. Simulation experiments show that the framework automatically learns eye-catchy presentations for relevant results. Experiments on real data show that simple instantiations of the framework already outperform leading algorithm in federated search result presentation. It means the framework can learn its own result presentation strategy purely from data, without even knowing the “probability ranking principle.”

A technique for improving text editing on touchscreen devices

We present a gesture-based technique for the efficient text editing on touchscreen devices. In order to define our technique, we ran a preliminary experiment and detected the most natural gestures that users choose when unconstrained. Users can perform the main operations such as select, move, copy, delete and paste directly on the text, thus making the editing technique independent from the text entry method (e.g. a soft keyboard). As an evaluation, we compared our gestural editing technique to the one available on most Android devices. The experimental results show that the gestural editing technique is more efficient when the text font size increases.

Welcome from the Editors: A Brief History of LCHS

Welcome from the Editors: A Brief History of LCHS

Welcome from the Editors: A Brief History of LCHS

Welcome from the Editors: A Brief History of LCHS

Laser display system for multi-depth screen projection scenarios.

Proposed is a laser projection display system that uses an electronically controlled variable focus lens (ECVFL) to achieve sharp and in-focus image projection over multi-distance three-dimensional (3D) conformal screens. The system also functions as an embedded distance sensor that enables 3D mapping of the multi-level screen platform before the desired laser scanned beam focused/defocused projected spot sizes are matched to the different localized screen distances on the 3D screen. Compared to conventional laser scanning and spatial light modulator (SLM) based projection systems, the proposed design offers in-focus non-distorted projection over a multi-distance screen zone with varying depths. An experimental projection system for a screen depth variation of 65cm is demonstrated using a 633nm laser beam, 3KHz scan speed galvo-scanning mirrors, and a liquid-based ECVFL. As a basic demonstration, an in-house developed MATLAB based graphic user interface is deployed to work along with the laser projection display, enabling user inputs like text strings or predefined image projection. The user can specify projection screen distance, scanned laser linewidth, projected text font size, projected image dimensions, and laser scanning rate. Projected images are shown highlighting the 3D control capabilities of the display, including the production of a non-distorted image onto two-depths versus a distorted image via dominant prior-art projection methods.

Thai Typefaces (Part 1)

Background: Regarding the growing elderly population, which several countries are experiencing right now, various typeface designs have been developed to address the need for increased legibility and visibility. Certainly, common factors that affect the well-being of the elderly are related to visual acuity. The universal design fonts (UD fonts) developed in Japan are regarded as a role model for the development of highly legible and visible Thai typefaces. As Thailand’s society matures, the concern for creating a Thai UD font based on human-centered design is ideal for the purpose of supporting elderly people as well as people with amblyopia and low vision Methods: As the first step to developing a Thai UD font, as a preliminary study, we qualitatively tested the tolerance of Thai characters under blurred conditions. We used the fifty Thai conventional text fonts in the boundary of ‘The Table of Thai Characters Relationship’ in the same character heights as stimuli. The stimuli simulated the visual acuity of people with poor vision at different blur levels. Results: From the tests, we have established the expected Thai confused pairs, as the assumptions. We found the simulated condition revealed many problems with the visibility and the legibility matters of Thai Characters, as the assumptions; however, these findings led to ideas and possible solutions, which may provide assistance for the approach to designing the first Thai UD font. Conclusions: After the simulated blurring was administered to the Thai conventional text fonts, visibility problems gave rise to discovering legibility issues - and consequently - an escalation of confused pairs. Therefore, the approach to developing the glyph of Thai UD fonts should apply two principles, EMPHASIS and REDUCTION (and others), for overall improved visibility and legibility.