STATISTICAL CHARACTERISTICS OF SLANT ANGLES IN HANDWRITTEN NUMERAL STRINGS AND EFFECTS OF SLANT CORRECTION ON SEGMENTATION

A novel and efficient method for correction of slant angles in handwritten numeral strings is proposed. For the first time, the statistical distribution of slant angles in handwritten numerals is investigated and the effects of slant correction on the segmentation of handwritten numeral strings are shown. In our proposed slant correction method, utilizing geometric features, a Component Slant Angle (CSA) is estimated for each connected component independently. A weighted average is then used to compute the String Slant Angle (SSA), which is applied uniformly to correct the slant of all the components in numeral strings. Our experimental results have revealed novel statistics for slant angles of handwritten numeral strings, and also showed that slant correction can significantly improve extraction of segmentation features and segmentation accuracy of touching numerals. Comparison between our slant correction algorithm and similar algorithms in the literature show that our algorithm is more efficient, and on average it has a faster running time.

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An Effective Slant Detection and Correction Method Based on the Tilted Rectangle Method for Telugu Manuscript Terms

International Journal of Information Technology Project Management ◽

10.4018/ijitpm.2021100103 ◽

2021 ◽

Vol 12 (4) ◽

pp. 25-37

Author(s):

Vijaya Kumar V. ◽

G. Bindu Madhavi ◽

V. Krishna Vakula

Keyword(s):

Efficient Method ◽

Correction Method ◽

Reverse Direction ◽

Connected Components ◽

Connected Component ◽

Slant Angle ◽

Shear Transformation ◽

Experimental Findings ◽

The Given ◽

Complex Characters

This paper proposes an efficient method called tilted rectangle (TR) for detecting and correcting of slant angle of the manuscript Telugu words (MTW). Telugu language is one of India's common languages spoken by over 80 million individuals. The complex characters are attached with some extra marks known as “maatras” and “vatthus,” and it is challenging to detect slant angle. The proposed TR method initially performs preprocessing and identifies a connected component within the given Telugu manuscript word. Then, it estimates the slant angle of each connected component by deriving connected slant lines on the boundary of each connected component. After this process, the proposed TR method estimates the entire word's overall slant angle from the average of estimated slant angle and height of all connected components. The correction of the word's slant angle is done in the reverse direction by applying a simple shear transformation. With 1000 manuscript records of three different kinds, the algorithm is tested. Experimental findings indicate the efficacy of the approach proposed.

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Efficient Method to Segment Objects from Images Based on Enhanced Connected Component Labeling algorithm

Iraqi Journal of Science ◽

10.24996/ijs.2018.59.1b.22 ◽

2018 ◽

Vol 59 (1B) ◽

Keyword(s):

Efficient Method ◽

Connected Component ◽

Connected Component Labeling ◽

Labeling Algorithm

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Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

Remote Sensing ◽

10.3390/rs13101927 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1927

Author(s):

Fuqin Li ◽

David Jupp ◽

Thomas Schroeder ◽

Stephen Sagar ◽

Joshua Sixsmith ◽

...

Keyword(s):

Coastal Waters ◽

Atmospheric Correction ◽

Correction Method ◽

In Situ Measurements ◽

Landsat 8 ◽

Correction Algorithm ◽

Simple Method ◽

North East ◽

The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

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Quantification and mitigation of the airborne limb imaging FTIR GLORIA instrument effects and uncertainties

10.5194/amt-2021-293 ◽

2021 ◽

Author(s):

Jörn Ungermann ◽

Anne Kleinert ◽

Guido Maucher ◽

Irene Bartolomé ◽

Felix Friedl-Vallon ◽

...

Keyword(s):

Infrared Imaging ◽

Infrared Detector ◽

Correction Algorithm ◽

Spectral Accuracy ◽

Flight Data ◽

Gain Error ◽

Laboratory Calibration ◽

Pointing Accuracy ◽

First Time ◽

Offset Error

Abstract. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an infrared imaging FTS spectrometer with a 2-D infrared detector operated on two high flying research aircrafts. It has flown on eight campaigns and measured along more than 300 000 km of flight track. This paper details our instrument calibration and characterization efforts, which in particular leverage almost exclusively in-flight data. First, we present the framework of our new calibration scheme, which uses information from all three available calibration measurements (two blackbodies and upward pointing deep space measurements). Part of this scheme is a new correction algorithm correcting the erratically changing non-linearity of a subset of detector pixels and the identification of remaining bad pixels. Using this new calibration, we derive a 1-σ bound of 1 % on the instrumental gain error and a bound of 30 nW cm−2 sr−1 cm on the instrumental offset error. We show how we can examine the noise and spectral accuracy for all measured atmospheric spectra and derive a spectral accuracy of 5 ppm, on average. All these errors are compliant with the initial instrument requirements. We also discuss, for the first time, the pointing system of the GLORIA instrument. Combining laboratory calibration efforts with the measurement of astronomical bodies during the flight, we can derive a pointing accuracy of 0.032°, which corresponds to one detector pixel. The paper concludes with a brief study on how these newly characterised instrumental parameters affect temperature and ozone retrievals. We find that, first, the pointing uncertainty and, second, the instrumental gain uncertainty introduce the largest error in the result.

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A method of hidden messages embedding in graphlike structures of a social network

Вычислительные технологии ◽

10.25743/ict.2018.23.12758 ◽

2018 ◽

Author(s):

И.В. Нечта

Keyword(s):

Social Networks ◽

Social Network ◽

Main Idea ◽

The Other ◽

Secret Message ◽

Automatic Registration ◽

Connected Component ◽

Single Node ◽

Empty Container ◽

First Time

Предложен новый метод передачи скрытых сообщений в социальных сетях на примере сети “Вконтакте”, позволяющий через структуру графа друзей пользователя внедрять секретные сообщения. Получены количественные оценки объема внедряемого сообщения в графы различного размера. Показана необходимость добавления избыточности во внедряемое сообщение. Представленный метод позволяет использовать другие графоподобные структуры социальной сети для внедрения скрытых сообщений. Purpose. This article addresses the construction of a new method for transmission of hidden messages in social networks. Methodology. The research employs methods of information theory, probability theory and mathematical statistics The Shannon entropy is used as the statistics for the analysis of an embedded message. Findings. The author proposed using the graphical structures of social networks as a container for the secret message transmission for the first time. As an example, the popular Vkontakte network is considered. The main idea of the method involves using the structure of the user’s friends graph to embed a secret message. Based on the available vertices (friends’ accounts), a complete graph is constructed, and its edges are enumerated. Each edge of the graph corresponds to one bit of the message being embedded: the bit is “1”, if the edge is present in the graph (one account in friends of the other), the bit is “0” if the edge is missing. To transfer the graph from one person to another, a key vertex is used. The specified vertex is connected by an edge with each connected component of the graph, which allows the graph to be transmitted using a single node and take into account all the vertices (including isolated ones). When retrieving a message, the key vertex and the edges connected to it are not considered. Conclusions. During the experimental research, it was shown that messages extracted from an empty container differ from the encrypted message by the probability distribution of bits. The necessity of adding redundancy to transmitted secret messages is shown with the purpose of “leveling” the statistical properties of an empty and filled container. The results of the experiment have showed that this method of steganography allows embedding a large amount of information into various social network structures represented in the form of a graph. It was noted in the paper that potentially “narrow” place of the algorithm is registration of new accounts. The restrictions imposed by the administration of some social networks for security purposes do not always allow automatic registration of new accounts, which makes the process of message embedding more difficult.

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Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. II. Smoothed intramolecular potentials

Acta Crystallographica Section B Structural Science Crystal Engineering and Materials ◽

10.1107/s2052520619005778 ◽

2019 ◽

Vol 75 (3) ◽

pp. 423-433 ◽

Cited By ~ 2

Author(s):

Isaac J. Sugden ◽

Claire S. Adjiman ◽

Constantinos C. Pantelides

Keyword(s):

Structure Prediction ◽

Weighted Average ◽

Lattice Energy ◽

Comparative Investigation ◽

Computational Effort ◽

Flufenamic Acid ◽

Computational Time ◽

Crystal Structure Prediction ◽

Efficient Representation ◽

First Time

The application of crystal structure prediction (CSP) to industrially relevant molecules requires the handling of increasingly large and flexible compounds. A revised model for the effect of molecular flexibility on the lattice energy that removes the discontinuities and non-differentiabilities present in earlier models (Sugden et al., 2016), with a view to improving the performance of CSP is presented. The approach is based on the concept of computing a weighted average of local models, and has been implemented within the CrystalPredictor code. Through the comparative investigation of several compounds studied in earlier literature, it is shown that this new model results in large reductions in computational effort (of up to 65%) and in significant increases in reliability. The approach is further applied to investigate, for the first time, the computational polymorphic landscape of flufenamic acid for Z′ = 1 structures, resulting in the successful identification of all three experimentally resolved polymorphs within reasonable computational time.

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Semantic Segmentation of Underwater Images Based on Improved Deeplab

Journal of Marine Science and Engineering ◽

10.3390/jmse8030188 ◽

2020 ◽

Vol 8 (3) ◽

pp. 188

Author(s):

Fangfang Liu ◽

Ming Fang

Keyword(s):

Semantic Segmentation ◽

Autonomous Driving ◽

Correction Method ◽

Target Object ◽

Original Method ◽

Indoor Navigation ◽

Fine Tuning ◽

Object Boundary ◽

Current State ◽

Segmentation Accuracy

Image semantic segmentation technology has been increasingly applied in many fields, for example, autonomous driving, indoor navigation, virtual reality and augmented reality. However, underwater scenes, where there is a huge amount of marine biological resources and irreplaceable biological gene banks that need to be researched and exploited, are limited. In this paper, image semantic segmentation technology is exploited to study underwater scenes. We extend the current state-of-the-art semantic segmentation network DeepLabv3 + and employ it as the basic framework. First, the unsupervised color correction method (UCM) module is introduced to the encoder structure of the framework to improve the quality of the image. Moreover, two up-sampling layers are added to the decoder structure to retain more target features and object boundary information. The model is trained by fine-tuning and optimizing relevant parameters. Experimental results indicate that the image obtained by our method demonstrates better performance in improving the appearance of the segmented target object and avoiding its pixels from mingling with other class’s pixels, enhancing the segmentation accuracy of the target boundaries and retaining more feature information. Compared with the original method, our method improves the segmentation accuracy by 3%.

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