Interline Spacing Research Articles

Characterization of Prickly Pear plantations in semi-arid zones! A green revolution in East Algeria: Case of the Tébessa region

The study carried out on the prickly pear shrub, in three potential production sites belonging to the commune of Ain Zerga district of Tébessa in the extreme east of the Algerian arid zone. The aim of this study was to try to interpret the main characteristics and sources of variability of this shrub of multiple interests. Carried out in 2023 on orchards planted with adult Opuntia ficus indica, developed in 45 orchards divided into 15 per site located in three localities, namely Henchir Lahdid, El Guefaifia, and Ouled Mebarek. The trees are grown extensively, with production starting in the last week of May. The cactus shrub reaches an equivalent production (10.23) kg and a production of 11,137.65kg/ha. At the time of the commercial harvest, indicated by the change in skin color, we carried out a random collection of 05 fruits per orchard, i.e. 75 fruits per site (225 fruits); these fruits were evaluated by various measurements. Shrub-specific variables such as fruit position in the canopy, cladode length, width, density, and inter-line spacing, number and weight of fruits per tree and per cladode, and annual productivity were studied. These variables per cactus shrub and fruit changed significantly as a function of climatic and edaphic environmental conditions, i.e. site and altitude, while the number of seeds/fruits was conditioned by volume. Fruit weight varied greatly within the same tree, influenced by the number of fruits per tree and the surface area of the cladodes; this variability decreased for cladodes bearing more than six fruits. Interception of climatic conditions (light) and cladode dry weight were the sources of variability in fruit weight, whereas Opuntia plant/hectare density had no effect on fruit quality.

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Potato peeling machines do not provide the necessary technological quality of the tuber cleaning process. The shovel separation system operating in heavy ground conditions must be equipped with a dynamic shredder of tubers. the driving mechanism of grinding and pipelining, operating on a dynamic principle, is located in front of the goiter of the potato peeling machine and covers the entire profile of the tuber. The ground chips cut from the tuber should be thrown into the aisle to reduce the amount of soil in the tuber-soil mass, the most purified tuber mass from the soil should be fed into the filter elevator. The analysis of the calculated value of the angle of installation of the knife shows that the optimal position of the knife in the range of rotation angles of the rotor depends only on the kinematic parameter. When justifying the parameters of a large-sized conveyor, determining the optimal value of the angle of installation of the knife is necessary, but still insufficient condition. A sufficient condition requires justification of the second parameter of the knife installation to ensure the simultaneous fulfillment of two conditions: cutting chips with an inclined slide and its ejection into the interline space. The installation condition of the knife is provided by sliding cutting, taking into account that it is necessary that the Earth chips be dumped into the aisle after cutting from the tuberous soil, to reduce the amount of soil in the tuberous-soil mass, a more purified tuberous mass from the soil is fed into the filter elevator.

Phonemic Harmony in Sufi Discourse

This paper aims to study the expressive values of linguistic sounds. This latter does not indicate meanings, but expresses emotions and suggesting meanings. This is what the recipient realizes with his phonetic intuition and knowledge of Arabic sounds and their characteristics through being able to build the harmony that occurs between the outputs of the sounds, their qualities and the meanings expressed. Different authentic or correct sounds (consonants and vowels) reflecting word expressions and long vowels then their appliance on some sample descriptive texts are studied. Concluding with a number of results, the most important of which is that the receiver is the one who builds the vocal harmony, and in this case, the relationship of sound with meaning is not arbitrary.
 Use of Times New Roman font in the title, size 10, bold, interline spacing 1, and font type in Times New Roman text, size 10, interline spacing 1,15 (this format applies to words keys). The summary is followed by keywords as cited in the article taking into account not to exceed 5 keywords.

Learning-free, divide and conquer text-line extraction algorithm for printed Arabic text with diacritics

The extraction of text lines from document images is a critical step in optical character recognition. It is still considered an open document analysis problem. The presence of numerous font variations, diacritics, overlapping, and touching text-lines presents a challenge to algorithms designed for machine-printed text. In this paper, we present a simple and robust text-line extraction algorithm for printed Arabic text. The presented method is divided into two stages: preprocessing and text-line extraction. It extracts text-lines efficiently, even in small font sizes, by utilizing baselines, projection profiles, and a top-down divide and conquer technique. The presented method is fast and efficient when dealing with non-uniform inter-line spacing and the text-line overlapping problem.A set of experiments were conducted on the collected dataset. The experiments revealed that the proposed method outperforms two baseline approaches, with an average error rate of 3% on Arabic text without diacritics and 11% on Arabic text with diacritics. Furthermore, the experiments demonstrate that the proposed algorithm has a simple computational running time, with an average running time of 0.087 s per document image.

Does BeeLine Reader’s gradient-coloured font improve the readability of digital texts for beginning readers?

In two reading experiments, we examined the efficacy of the commercial reading assistance application BeeLine Reader which colours the letters of digital texts in gradients. According to its developers, BeeLine Reader increases reading speed, improves comprehension, and makes reading more enjoyable. We tested these hypotheses for second- and third-grade pupils (6–9 years old), assessing the influence of BeeLine Reader in several layouts in which we varied other features that are known to impact the reading processes of beginning readers (line spacing, line length, text segmentation). In comparison to control texts with a standard black font, reading time advantages for BeeLine texts emerged for pupils in second grade (not in third grade) when they read texts with long lines and little inter-line spacing. However, when second-grade readers processed texts that were optimized for their reading level (texts with short lines and sufficient inter-line spacing) they displayed a slower reading pace in texts with a BeeLine font than in texts with a black font. Furthermore, BeeLine texts may hamper comprehension for third-grade readers and were rated as more difficult and less convenient to process than texts with a black font. In conclusion, the visual anchors offered by BeeLine Reader may be useful for some beginning readers in some situations but the application can also impede the readability of texts. These findings emphasize that claims made for digital reading applications should be formally tested if they are going to be introduced into educational settings.

Femtosecond-laser-assisted spatial cell adhesion to microstructured surface geometry

This article discusses the adhesion of C2C12 mouse myoblast cells to a microstructured polydimethylsiloxane (PDMS) surface patterned using femtosecond laser pulses. The wettability of the PDMS surface can be controlled by changing the writing-pulse energy; a hydrophilic surface is produced by low pulse energy, whereas high pulse energies lead to a superhydrophobic surface. The surface topography also varies with pulse energy. Images acquired with scanning electron microscopy show clear lines at low pulse energy, whereas at high energies, the lines are completely deformed by the presence of micro- and nano-structures. Thus, selective cell growth in the modified regions is affected by the energy of the laser pulses used for surface modification. In addition, the surface geometry (e.g., lines vs grids) of the modified regions affects the shape and alignment of C2C12 cells. Thus, we investigate the degree of cell alignment to modified lines fabricated with the same pulse energy and writing speed but with different inter-line spacings. The degree of alignment is quantified by the average value of a second-order Legendre polynomial. The results reveal that the degree of alignment of C2C12 cells to the surface lines decreases with the increase in spacing between lines.

Distance transform based text-line extraction from unconstrained handwritten document images

Text-line extraction (TLE) is the process of segmenting a document page into lines of text for processing by modules such as language and writer identification or Optical Character Recognition (OCR). Designing of an appropriate TLE method is always a challenging research problem especially in the domain of unconstrained handwritten documents. This is because of the vast number of potential interactions between the text lines. For example, these lines are not always straight, lines written close to each other can overlap with ascenders and descenders, and lines can interact with other content on the page. In this paper, we present a novel language-independent text-line extraction method for unconstrained handwritten documents which handles complexities such as touching and multi-skewed text lines, overlapping characters and irregular inter-line spacing. Our method preprocesses the document pages using a distance transform based method and uses a novel path detection algorithm to separate individual text-line. The proposed method has been tested on six standard datasets which are publicly available and the experimental results show that our method achieves a promising accuracy over state-of-the-art TLE methods.

Detecting Text Baselines in Historical Documents With Baseline Primitives

Previous deep learning based approaches to text baseline detection in historical documents usually take it as a semantic segmentation task. These methods adopt a fully convolutional neural network to predict baseline pixels first and then group them into lines by heuristic post-processing steps, which tends to suffer from a wrongly merged or wrongly split problem owing to limited context information provided by pixels. To address these issues, we introduce the concept of a baseline primitive, which is defined as a virtual bounding box centered at each baseline pixel. After baseline primitive detection, a relation network is used to predict a link relationship for each pair of primitives. Consequently, text baselines are generated by detecting baseline primitives and grouping them with the corresponding link relationships. Owing to the design of baseline primitives, wider context information can be leveraged to improve link prediction accuracy. Therefore, our approach can effectively detect text baselines with small inter-line or large inter-word spacing. Quantitative experimental results demonstrate the effectiveness of the proposed baseline primitive design. Our approach achieves state-of-the-art performance on two public benchmarks, namely cBAD 2017 and cBAD 2019.

Система маркирования документов для проведения расследований при их утечке

This paper presents a confidential text documents leakage investigation system, focused on leak channels by documents printing and screen photographing. Internal intruders may print confidential document, take paper copy out of protected perimeter, make document image by scanner and perform anonymous leak. Also, intruders may take a photo of printed confidential document or displayed on workstation screen using personal mobile phone. Described leakage channels are weakly covered by traditional DLP systems that are usually used by enterprises for confidential information leak protection. Digital watermark (DWM) embedding is chosen as a document protection mechanism by implying changing of document image visual representation. In case of confidential document anonymous leak embedded DWM would enable the employee to determine what leak intentionally or by security protocol violation. System architecture consists of different type components. Employees’ workstation components provide DWM embedding into documents, which are sent for printing or displayed on screen. Information about watermark embedding is sent to a remote server that aggregates marking facts and provides it to security officer during investigation. Text document marking algorithms are developed, which embed DWM into printed and displayed on screen documents. Screen watermark is embedded into interline space interval, information is encoded by sequence of lightened and darkened spaces. DWM embedding into printed documents is implemented by three algorithms: horizontal and vertical shift based, font fragments brightness changing based. Algorithms testing methodology is developed in view of the production environment, that helped to evaluate the application area of algorithms. Besides, intruder model was formulated, system security was evaluated and determined possible attack vectors.

Маркирование текстовых документов на экране монитора посредством изменения яркости фона в областях межстрочных интервалов

One of the most common ways documents leak is taking a picture of document displayed on the screen. For investigation of such cases data leakage prevention technologies including screen watermarking are used. The article gives short review on the problem of screen shooting watermarking and the existing research results. A novel approach for watermarking text images displayed on the screen is proposed. The watermark is embedded as slight changes in luminance into the interline spacing of marked text. The watermark is designed to be invisible for human eye but still able to be detected by digital camera. An algorithm for extraction of watermark from the screen photo is presented. The extraction algorithm doesn’t need the original image of document for successful extraction. The experimental results show that the approach is robust against screen-cam attacks, that means that the watermark stays persistent after the process of taking a photo of document displayed on the screen. A criterion for watermark message extraction accuracy without knowledge about the original message is proposed. The criterion represents the probability that the watermark was extracted correctly.

ReLaText: Exploiting visual relationships for arbitrary-shaped scene text detection with graph convolutional networks

We introduce a new arbitrary-shaped text detection approach named ReLaText by formulating text detection as a visual relationship detection problem. To demonstrate the effectiveness of this new formulation, we start from using a “link” relationship to address the challenging text-line grouping problem firstly. The key idea is to decompose text detection into two subproblems, namely detection of text primitives and prediction of link relationships between nearby text primitive pairs. Specifically, an anchor-free region proposal network based text detector is first used to detect text primitives of different scales from different feature maps of a feature pyramid network, from which a text primitive graph is constructed by linking each pair of nearby text primitives detected from a same feature map with an edge. Then, a Graph Convolutional Network (GCN) based link relationship prediction module is used to prune wrongly-linked edges in the text primitive graph to generate a number of disjoint subgraphs, each representing a detected text instance. As GCN can effectively leverage context information to improve link prediction accuracy, our GCN based text-line grouping approach can achieve better text detection accuracy than previous text-line grouping methods, especially when dealing with text instances with large inter-character or very small inter-line spacing. Consequently, the proposed ReLaText achieves state-of-the-art performance on five public text detection benchmarks, namely RCTW-17, MSRA-TD500, Total-Text, CTW1500 and DAST1500.

Design Guidelines for Schematizing and Rendering Haptically Perceivable Graphical Elements on Touchscreen Devices

ABSTRACT This paper explores the viability of new touchscreen-based haptic/vibrotactile interactions as a primary modality for perceiving visual graphical elements in eyes-free situations. For touchscreen-based haptic information extraction to be both accurate and meaningful, the onscreen graphical elements should be schematized and downsampled to: (1) maximize the perceptual specificity of touch-based sensing and (2) account for the technical characteristics of touchscreen interfaces. To this end, six human behavioral studies were conducted with 64 blind and 105 blindfolded-sighted participants. Experiments 1–3 evaluated three key rendering parameters that are necessary for supporting touchscreen-based vibrotactile perception of graphical information, with results providing empirical guidance on both minimally detectable and functionally discriminable line widths, inter-line spacing, and angular separation that should be maintained. Experiments 4–6 evaluated perceptually-motivated design guidelines governing visual-to-vibrotactile schematization required for tasks involving information extraction, learning, and cognition of multi-line paths (e.g., transit-maps and corridor-intersections), with results providing clear guidance as to the stimulus parameters maximizing accuracy and temporal performance. The six empirically-validated guidelines presented here, based on results from 169 participants, provide designers and content providers with much-needed guidance on effectively incorporating perceptually-salient touchscreen-based haptic feedback as a primary interaction style for interfaces supporting nonvisual and eyes-free information access.

Redundancy masking: The loss of repeated items in crowded peripheral vision.

Crowding is the deterioration of target identification in the presence of neighboring objects. Recent studies using appearance-based methods showed that the perceived number of target elements is often diminished in crowding. Here we introduce a related type of diminishment in repeating patterns (sets of parallel lines), which we term “redundancy masking.” In four experiments, observers were presented with arrays of small numbers of lines centered at 10° eccentricity. The task was to indicate the number of lines. In Experiment 1, spatial characteristics of redundancy masking were examined by varying the inter-line spacing. We found that redundancy masking decreased with increasing inter-line spacing and ceased at spacings of approximately 0.25 times the eccentricity. In Experiment 2, we assessed whether the strength of redundancy masking differed between radial and tangential arrangements of elements as it does in crowding. Redundancy masking was strong with radially arranged lines (horizontally arranged vertical lines), and absent with tangentially arranged lines (vertically arranged horizontal lines). In Experiment 3, we investigated whether target size (line width and length) modulated redundancy masking. There was an effect of width: Thinner lines yielded stronger redundancy masking. We did not find any differences between the tested line lengths. In Experiment 4, we varied the regularity of the line arrays by vertically or horizontally jittering the positions of the lines. Redundancy masking was strongest with regular spacings and weakened with decreasing regularity. Our experiments show under which conditions whole items are lost in crowded displays, and how this redundancy masking resembles—and partly diverges from—crowded identification. We suggest that redundancy masking is a contributor to the deterioration of performance in crowded displays with redundant patterns.

Text-line extraction from handwritten document images using GAN

Text-line extraction (TLE) from unconstrained handwritten document images is still considered an open research problem. Literature survey reveals that use of various rule-based methods is commonplace in this regard. But these methods mostly fail when the document images have touching and/or multi-skewed text lines or overlapping words/characters and non-uniform inter-line space. To encounter this problem, in this paper, we have used a deep learning-based method. In doing so, we have, for the first time in the literature, applied Generative Adversarial Networks (GANs) where we have considered TLE as image-to-image translation task. We have used U-Net architecture for the Generator, and Patch GAN architecture for the discriminator with different combinations of loss functions namely GAN loss, L1 loss and L2 loss. Evaluation is done on two datasets: handwritten Chinese text dataset HIT-MW and ICDAR 2013 Handwritten Segmentation Contest dataset. After exhaustive experimentations, it has been observed that U-Net architecture with combination of the said three losses not only produces impressive results but also outperforms some state-of-the-art methods.

Text baseline detection, a single page trained system

Nowadays, there are a lot of page images available and the scanning process is quite well resolved and can be done industrially. On the other hand, HTR systems can only deal with single text line images. Segmenting pages into single text line images is a very expensive process which has traditionally been done manually. This is a bottleneck which is holding back any massive industrial document processing. A baseline detection method will be presented here1. The initial problem is reformulated as a clustering problem over a set of interest points. Its design aim is to be fast and to resist the noise artifacts that usually appear in historical manuscripts: variable interline spacing, the overlapping and touching of words in adjacent lines, humidity spots, etc. Results show that this system can be used to massively detect where the text lines are in pages. Highlight: This system reached second place in the Icdar 2017 Competition on Baseline Detection (see Table 1).

An approach to a robust watermark extraction from images containing text

This paper presents an approach to a robust watermark extraction from images containing text. Data extraction based on developed approach to robust watermark embedding into text data, characterizing by conversion invariance of text data into an image format. The comparative analysis of existing approaches of steganographic data embedding into text data is carried out, their advantages and disadvantages are determined. The choice of groups to steganographic data embedding methods based on text formatting is justified. As an embedding algorithm is determined approach based on interline space shifting. The block diagram and the description of the developed algorithm of data embedding into text data are given. An experimental estimation of the embedding capacity and perceptual invisibility of the developed data embedding approach was carried out. An approach to extract embedded information from images containing a robust watermark, based on the existing limitations, has been developed. The Radon transform is chosen as the basic extraction procedure of embedded information, allowing to extract values of the interline spacing. An approach based on Gaussian mixture model separating to isolate the values of the bits was chosen. The limits of the retrieval of embedded data have been experimentally established, and the robustness of the developed embedding approach to the implementation of various transformations has been estimated. The following parameters of robustness developed approach are defined: rotation of an image containing embedded data at any angle; scaling an image with a scaling factor not exceeding 1.5; conversion to any bitmap format; the application of a median filter to an image with a convolution core limit of not more than 9, a Gaussian blur filter with a blurring limit not exceeding 8 and an average filter with a convolution kernel limit of not more than 5.

The effects of visual crowding, text size, and positional uncertainty on text legibility at a glance

Reading at a glance, once a relatively infrequent mode of reading, is becoming common. Mobile interaction paradigms increasingly dominate the way in which users obtain information about the world, which often requires reading at a glance, whether from a smartphone, wearable device, or in-vehicle interface. Recent research in these areas has shown that a number of factors can affect text legibility when words are briefly presented in isolation. Here we expand upon this work by examining how legibility is affected by more crowded presentations. Word arrays were combined with a lexical decision task, in which the size of the text elements and the inter-line spacing (leading) between individual items were manipulated to gauge their relative impacts on text legibility. In addition, a single-word presentation condition that randomized the location of presentation was compared with previous work that held position constant. Results show that larger text was more legible than smaller text. Wider leading significantly enhanced legibility as well, but contrary to expectations, wider leading did not fully counteract decrements in legibility at smaller text sizes. Single-word stimuli presented with random positioning were more difficult to read than stationary counterparts from earlier studies. Finally, crowded displays required much greater processing time compared to single-word displays. These results have implications for modern interface design, which often present interactions in the form of scrollable and/or selectable lists. The present findings are of practical interest to the wide community of graphic designers and interface engineers responsible for developing our interfaces of daily use.

Screening efficacy of a simplified logMAR chart

Background: Snellen acuity charts are the most commonly used method for visual acuity (VA) testing in screening programmes despite comparative studies verifying that the logarithm of minimum angle of resolution (logMAR) acuity measurement charts are more accurate than the Snellen chart acuity measurements. LogMAR acuity measurement charts however are not well implemented in routine clinical practice because of the increased testing time and the complexity of scoring. To implement the logMAR method in a screening programme, there has to be some simplification of it.Aim: This study evaluates the efficacy of a simplified logMAR chart, designed for VA testing over the conventional Snellen chart, in a school-based vision-screening programme.Methods: We designed a simplified logMAR chart by employing the principles of the Early Treatment Diabetic Retinopathy Study (ETDRS) chart in terms of logarithmic letter size progression, inter-letter spacing, and inter-line spacing. Once the simplified logMAR chart was validated by students in the Elite school vision-screening programme, we set out to test the chart in 88 primary and middle schools in the Tiruporur block of Kancheepuram district in Tamil Nadu. One school teacher in each school was trained to screen a cross-sectional population of 10 354 primary and secondary school children (girls: 5488; boys: 4866) for VA deficits using a new, simplified logMAR algorithm. An experienced paediatric optometrist was recruited to validate the screening methods and technique used by the teachers to collect the data. Results: The optometrist screened a subset of 1300 school children from the total sample. The optometrist provided the professional insights needed to validate the clinical efficacy of the simplified logMAR algorithm and verified the reliability of the data collected by the teachers. The mean age of children sampled for validation was 8.6 years (range: 9–14 years). The sensitivity and the specificity of the simplified logMAR chart when compared to the standard logMAR chart were found to be 95% and 98%, respectively. Kappa value was 0.97. Sensitivity of the teachers’ screening was 66.63% (95% confidence interval [CI]: 52.73–77.02) and the specificity was 98.33% (95% CI: 97.49–98.95). Testing of VA was done under substandard illumination levels in 87% of the population. A total of 10 354 children were screened, 425 of whom were found to have some form of visual and/or ocular defect that was identified by the teacher or optometrist.Conclusion: The simplified logMAR testing algorithm proved to be less time consuming than the standard logMAR test. This suggests that the simplified logMAR chart is effective in vision-screening programmes and would be a reliable alternative to the standard logMAR chart and therefore replace the use of Snellen chart acuity tests in vision-screening programmes. The study also showed that non-healthcare providers, such as teachers, can reliably administer the simplified logMAR test.Keywords: vision screening; school children; vision screening standards; screening reliability

Bioinspired electrohydrodynamic ceramic patterning of curved metallic substrates

Template-assisted electrohydrodynamic atomisation (TAEA) has been used for the first time to pattern curved metallic surfaces. Parallel lines of ceramic titania (TiO2) were produced on titanium substrates, convex and concave with diameters of ~25 mm, at the ambient temperature. Optimal results were obtained with 4 wt% TiO2in ethanol suspension deposited over 300 s during stable cone-jetting at 20 µl/min, 10kV and collection distance 80 mm. A high degree of control over pattern line width, interline spacing and thickness were achieved. Nanoindentation load-displacement curves were continuous for the full loading and unloading cycle, indicating good adhesion between pattern and substrate. At a loading rate of 1 μN/s and a hold time of 1 s, pattern hardness decreased as load increased up to 7 μN and remained at 0·1 GPa up to higher loads. Elastic modulus behaved similarly, and both were not sensitive to loading rate. The effect of heat treatment to further consolidate the patterned deposits was also investigated. Hardness of the patterns was not markedly affected by heating. This work shows that TAEA is highly controllable and compatible on a range of substrate geometries. Extending TAEA capabilities from flat to curved surfaces, enabling the bioactive patterning of different surface geometries, takes this technology closer to orthopaedic engineering applications.

ReadingMate

The aim of this study was to investigate the effects of font size, interline spacing, and a technology called ReadingMate on the letter-counting task performance of users running on a treadmill. Few researchers have investigated how runners read text while running on a treadmill. Our previous studies showed that ReadingMate had positive effects on the reading-while-running experience; however, the effect of other text conditions (i.e., font size and interline spacing) and the interplay between ReadingMate and such text conditions on the letter-counting task performance are not clearly understood. Fifteen participants were recruited for the experiment. There were three main factors: display types (normal and ReadingMate), font sizes (8, 12, 16, and 20 point), and interline spacing (1.0x, 1.5x, 2.0x, and 2.5x). The researchers employed a letter-counting task. The performance was measured regarding task performance time, success rate of counting the target letter f and number of give-ups. Overall, the letter-counting task performance while running on a treadmill improved as font size and interline spacing increased, as expected. ReadingMate was more effective than normal display particularly when text was displayed in a small font size and with dense interline spacing. When text must be displayed in a small font size and with dense interline spacing, ReadingMate can be used to improve the users' task performance. Practical applications of ReadingMate include improving the text-reading experience in shaky environments, such as in aviation, construction, and transportation.