Digital Curves Research Articles

THE CURVE ARC AS A STRUCTURE ELEMENT OF AN OBJECT CONTOUR IN THE IMAGE TO BE RECOGNIZED

Context. The proposed article relates to the field of visual information processing in a computer environment, more precisely to the determination the parameters of the interest object in the image, in particular, the contour of the interest object In most cases, the contour of an object is a simply connected sequence of curve arcs.
 Objective. The purpose and subject of the study is to find and to propose such a definition of the digital curve arc, as the most important element of the object contour in the recognizable image, which does not contradict modern neurophysiological conceptions about visual perception, and to recognize the object contour as a sequence of the digital curve arcs.
 Method. The representation of the image in the form of a structural model is used, one of the structural elements of which is the contour of the object, consisting of digital curve arcs. Also, the image is considered as a cellular complex which corresponds to modern ideas about human visual perception.
 Results. The new definition for arc of a digital curve as a sequence of digital straight segments is proposed, which does not contradict to modern concepts of neurophysiology. In contrast to the known definitions of a curve arc, the proposed definition of a digital curve arc makes it possible to determine the start and end points of the arc. According to the description of the contour of an object as a simply connected closed sequence of line segments, it is proposed to construct a description of the contour as a sequence of arcs of digital curves.
 Conclusions. The use of the proposed definition of the digital curve arc in image processing makes it possible to recognize the contour of an object in an image and present it in a form close to visual perception. For best results, the use of variable resolution in image processing algorithms is recommended.

Classification of Long-Bone Fractures Using Modified Faster RCNN for X-Ray Images

Objectives: Methods in machine learning have been shown to be an essential tool for the diagnosis and treatment of disease. The scientists are constantly looking for new technology that might improve current clinical practise. One of the most well-liked study fields continues to be computerized bone fracture identification and categorization. Furthermore, identifying cracks and determining where they occur have been challenges for historically developed approaches for the long bone fracture method. Methods: We propose a new approach for automatic fracture detection in X-Ray images. This approach is built on top of two-stage fracture detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The described procedure is divided into four main steps: X-ray images are used to: I identify the bone contour; (ii) identify fracture-points or fractures; (iii) find a similar set of shapes that are compatible with the identification of cracks; and (iv) classify and thoroughly evaluate the fracture-type using bounding box. Finding: The resolution process uses the stretched numerical conventional line techniques (RDS), arcs, discrete curvature, and shape directory, among other mathematical characteristics of digital curves. We assessed the suggested model’s performance in terms of classification and detection. We divide x-ray pictures of bone fractures into 2 groups, fracture and non-fracture, and we also use a rectangular box to identify the location of fractures. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. Novelty: This study develops a new approach to automatically and accurately detect fractures in X-Ray images. The proposed approach is developed on the basis of Faster R-CNN algorithm with a major modification for the task of rotated bounding box prediction. Keywords: Long bone; X-Ray images; Classification; Detection; Faster RCNN; Fracture; Non-Fracture; Types

The counterfeit degree certificate: application of blockchain technology in higher education in India

PurposeIn this work-in-progress, the application of blockchain technology (BT) in higher education in India – involving academic institutions, students and verifiers – in the wake of fake degrees (racket) being issued at a large scale from universities across the country is being investigated. This paper considers providing new methods of database system in education, and implementing the new BT in education can increase transparency and security in the education system.Design/methodology/approachThis study used interview methodology (asking interview participants a series of informal questions to obtain knowledge).FindingsPrivate and public sector organizations have many challenges to overcome in synchronizing and aligning their digital transformation efforts to enable the network effects to take hold. India’s policymakers, civil society leaders, senior business leaders and entrepreneurs are building strong clusters to help the country be the leader of the next era of the internet as a platform that helps transform human affairs for the benefit of the citizens. Executives can contribute to the digital ecosystem by creating open and collaborative cultures where knowledge and innovation are shared with the industry for the benefit of the masses and, more so, to establish quality and communication standards. They also can contribute by staying open to change, embracing digital adoption and transformation within their management models and infrastructure. It is time for institutions to rethink their processes and governance structures to become more agile and innovative players. The success of a harmonious digital identity ecosystem relies on staying ahead of the organization’s digital curve. As a first step to provide better quality in the provision of public services, Secure Key Technologies’ blockchain-based ecosystem (securekey.com) allows multiple partners to strengthen the authentication and provides identity attribute validation as a fabric of trust and as a solid foundation to embrace a new digital era. Secure Key Technologies’ vision for the future of digital identities redefines the ways both consumers and businesses approach identity verification and the sharing of key personal information. The challenges identified in the education system be it the difficulty in authenticating certifications and documents, tracking intellectual property and in accessibility can be better managed through blockchain implementation.Originality/valueDigital certificates produced using blockchains are the most secure and efficient method being adopted by many countries across the globe (Grech and Camilleri, 2017). Tamper-proof blockchain records consist of three components or layers: the first contains the signed hash of the content, the second contains all the data and images and the third is the presentation and styling of the data. The verification process is relatively simple; the hash of the recipient is compared to the hash stored on the blockchain if they match the document is verified.

New Algorithms for Electronic Digital Elliptic Curves

New Algorithms for Electronic Digital Elliptic Curves

A Jordan curve theorem for 2-dimensional tilings

The classical Jordan curve theorem for digital curves asserts that the Jordan curve theorem remains valid in the Khalimsky plane. Since the Khalimsky plane is a quotient space of R2 induced by a tiling of squares, it is natural to ask for which other tilings of the plane it is possible to obtain a similar result. In this paper we prove a Jordan curve theorem which is valid for every locally finite tiling of R2. As a corollary of our result, we generalize some classical Jordan curve theorems for grids of points, including Rosenfeld's theorem.

Introduction to the Special Issue ‐ The internet, social media and trade union revitalization: Still behind the digital curve or catching up?

AbstractThis article introduces the special issue of New Technology, Work and Employment titled “The Internet, Social Media and Trade Union Revitalization: Still Behind the Digital Curve or Catching Up?” The objectives of this special issue are threefold. First, to develop an analytical framework that can help researchers assess the role that internal and external factors play in mediating the nature and scope of union experimentation with new information and communication technologies (ICTs) and its contribution to the outcomes of revitalisation. Second, to present methods and concepts that are new to this area of research. Third, to generate empirical insight into how the various actors that constitute the trade union movement (e.g. worker councils, union confederations, trade unions, and union‐led coalitions) can and are using the internet, social media and artificial intelligence as a means of revitalisation. Taken together the geographical scope of the articles range from single‐country cases studies in Germany, the UK and Canada, to a cross‐national case study in Australia and the USA, and a comparative study across Europe. In terms of ICTs, attention is given to websites, Twitter, Facebook, YouTube and an AI chatbot.

Digital Jordan Curves and Surfaces with Respect to a Closure Operator

In this paper, we propose new definitions of digital Jordan curves and digital Jordan surfaces. We start with introducing and studying closure operators on a given set that are associated with n-ary relations (n > 1 an integer) on this set. Discussed are in particular the closure operators associated with certain n-ary relations on the digital line ℤ. Of these relations, we focus on a ternary one equipping the digital plane ℤ2 and the digital space ℤ3 with the closure operator associated with the direct product of two and three, respectively, copies of this ternary relation. The connectedness provided by the closure operator is shown to be suitable for defining digital curves satisfying a digital Jordan curve theorem and digital surfaces satisfying a digital Jordan surface theorem.

Fixed Point Sets of Digital Curves and Digital Surfaces

Given a digital image (or digital object) (X,k), we address some unsolved problems related to the study of fixed point sets of k-continuous self-maps of (X,k) from the viewpoints of digital curve and digital surface theory. Consider two simple closed k-curves with li elements in Zn, i∈{1,2},l1⪈l2≥4. After initially formulating an alignment of fixed point sets of a digital wedge of these curves, we prove that perfectness of it depends on the numbers li,i∈{1,2}, instead of the k-adjacency. Furthermore, given digital k-surfaces, we also study an alignment of fixed point sets of digital k-surfaces and digital wedges of them. Finally, given a digital image which is not perfect, we explore a certain condition that makes it perfect. In this paper, each digital image (X,k) is assumed to be k-connected and X♯≥2 unless stated otherwise.

Fixed Point Sets of k-Continuous Self-Maps of m-Iterated Digital Wedges

Let Ckn,l be a simple closed k-curves with l elements in Zn and W:=Ckn,l∨⋯∨Ckn,l︷m-times be an m-iterated digital wedges of Ckn,l, and F(Conk(W)) be an alignment of fixed point sets of W. Then, the aim of the paper is devoted to investigating various properties of F(Conk(W)). Furthermore, when proceeding with this work, this paper addresses several unsolved problems. To be specific, we firstly formulate an alignment of fixed point sets of Ckn,l, denoted by F(Conk(Ckn,l)), where l(≥7) is an odd natural number and k≠2n. Secondly, given a digital image (X,k) with X♯=n, we find a certain condition that supports n−1,n−2∈F(Conk(X)). Thirdly, after finding some features of F(Conk(W)), we develop a method of making F(Conk(W)) perfect according to the (even or odd) number l of Ckn,l. Finally, we prove that the perfectness of F(Conk(W)) is equivalent to that of F(Conk(Ckn,l)). This can play an important role in studying fixed point theory and digital curve theory. This paper only deals with k-connected digital images (X,k) such that X♯≥2.

Reference Trajectory Modification Based on Spatial Iterative Learning for Contour Control of Two-Axis NC Systems

Contour error is a main factor that affects the quality of products in numerical control (NC) machining. This article presents a contour control strategy based on digital curves for high-precision control of computer numerical control (CNC) machines. A contour error estimation algorithm is presented for digital curves based on a geometrical method. The dynamic model of the motion control system is transformed from time domain to space domain because the contour error is dependent on space instead of time. Spatial iterative learning control (sILC) is developed to reduce the contour error, by modifying the reference trajectory in the form of G code. This allows system improvement without interference of low-level controllers so it is applicable to many commercial controllers where interpolators and feed-drive controllers cannot be altered. The effectiveness of this method is verified by experiments on a NC machine, which have shown good performance not only for smooth trajectories but also for large curvature trajectories.

Promising mathematical methods for early diagnosis of human circulatory disorders

The aim of the study is elaboration of efficient mathematical models for early diagnostics of the cardiovascular diseases based on the blood flow rate Q(t) curves measured noninvasively in different parts of human body. Ultrasound, rheography, magnetic resonance imaging techniques could be useful for the purpose. In this paper a set of rheographic curves Q(t) has been measured in the abdominal aorta Qc(t), left and right upper Q1(t) and Q2(t) and lower Q3(t) and Q4(t) extremities of 36 volunteers of the age 36-65. Correlation analysis has been used for each pair {Qi(t),Qj(t)} of the measured discrete signals and some statistical indexes have been found significant for reliable early diagnostics of blood insufficiency due to arterial narrowing, improper control and age-related degenerative changes in the blood vessel walls. It is shown that in most individuals the digital curves Q1(t) and Q2(t) well correspond to a linear correlation with a small dispersion, while the curves Q3(t) and Q4(t) are usually weakly correlated, characterized by some time shift between them, significant dispersion and in some patients have unpredictable (chaotic) dynamics. Covariance indices for all the pairs {Qi(t),Qj(t)} of the curves, their spectra and the Lyapunov exponents are calculated. It is shown that in young healthy subjects all the covariances , the spectrum has 3-4 fundamental harmonics, and all Lyapunov exponents <0 that corresponds to regular or quasi-regular dynamics. In most elderly subjects the covariances , especially in the curves measured in the lower extremities, the spectra are complicated, and have positive Lyapunov exponents > 0, that corresponds to the possibility of chaotic dynamics. In the young healthy individuals without diseases and age-related degenerative changes of the cardiovascular system, there are some complications of the spectrum, the presence of both <0 and > 0. Thus, the values , and spectrum of the curves can be important parameters for early diagnosis of age-related changes and circulatory disorders. Their prompt computations can be easily done on any type of cheap and noninvasive ultrasound or impedance rheography curves. Regular measurements and accumulation of such curves in a personal database will increase the quality of individual and population healthcare.

Robust Corner Finding Based on Multi-Scale K-Cosine Angle Detection

Corner is widely utilized in computer vision and image processing. As a representative contour-based corner detection algorithm, RJ detector is first proposed to use the K-cosine to estimate curvature of digital curves for corner finding. However, such influential approach is quite sensitive to the geometric transformations and noise due to its dynamic smoothing scale. To overcome this drawback and enhance its performance further, this paper presents a multi-scale version of RJ detector. First, we adopt fixed region of radius (RoS) to avoid its sensitiveness to geometric transformations; second, the technique of scale product is employed to enhance curvature extreme peaks and suppress noise for improving localization. Extensive experiments on several corner detection datasets are conducted for evaluating its performances. And the experimental results demonstrate that such simple idea endows RJ an incredible improvement and MSRJ achieves the competitive performance compared with state-of-the-arts corner detectors under measure metrics of average repeatability and localization error.

Hand Drawing in the Definition of the First Digital Curves

The first digitization systems successfully used in curves with origin in mathematical calculations or experimental tests proved useless when they were the result of heuristic methods developed under aesthetic criteria. Renault engineer Pierre Bézier and Citroën engineer Paul de Casteljau found the solution by focusing on the period of ideation of shapes and not on their subsequent translation and integration into the digital domain, studying the working methods of designers and incorporating in the mathematical definition of their curves the own actions of drawing, understood as basic instrumental support in creative processes. This article traces and analyzes the strong relationship between Bézier’s original approach and the procedures driving the manual stroke as the main reason for the consolidation of his graphic proposal as the most effective model for the hand drawing of digital curves and its inclusion since that time and to the present day in the software used by architects.

Polygonal approximation based on coarse-grained parallel genetic algorithm

This paper proposes to apply coarse-grained parallel genetic algorithm (CGPGA) to solve polygonal approximation problem. Chromosomes are used to represent digital curves and genes correspond to points of curves. This method divides the whole population into several subpopulations, each of which performs evolutionary process independently. After every migration interval number of generations, these subpopulations exchange their information with each other. Inspired by the designing theory of ensemble learning in machine learning, this paper further improves the basic CGPGA through adopting different but effective genetic algorithms, respectively, in different subpopulations. Both the diversity among different subpopulations and the accuracy in each individual subpopulation are ensured. Experimental results, based on four benchmark curves and four real image curves extracted from the lake maps, show that the basic CGPGA outperforms the used genetic algorithm, and further the improved CGPGA (ICGPGA) is more effective than the basic CGPGA, in terms of the quality of best solutions, the average solutions, and the variance of best solutions. Especially for those larger approximation problems, the ICGPGA is more remarkably superior to some representative genetic algorithms.

An Efficient Image Downsampling Technique Using Genetic Algorithm And Digital Curvelet Transform

Propelled pictures are used everywhere and are definitely not hard to manage and change in view of the availability of various picture getting ready and adjusting programming. Repeat the image to a lesser extent and change the look of the image. This can be useful at times when the original version of the original will give you a slim version of the film. There are several methods of image downsampling. This sheet uses performance capabilities for a collage based on digital curve transfers and generic algorithms. Genetic Algorithm (GA) is attached by the Digital Curvelet Transform (DCT). Originally DCT The length of the map decreases by using. Using this reduced map, gateways and entry worth are coordinated by the utilization of hereditary estimation. From the appraisal of results, it will when all is said in done be picked that the proposed method is quick and exact.

Beyond the digital Jordan curve: Unconstrained simple pixel-based raster relations

Abstract Artificial intelligence and satellites have brought spatial-image interpretation to the forefront. Over the past two decades, the literature has provided three distinct methods for identifying and classifying the boundary of raster objects: the digital Jordan curve, the hyper-raster, and a marginal approach. While each approach has its own merits and drawbacks, there should be methods by which to convert one representation to another. This, however, is currently unattainable as the digital Jordan curve approach and the hyper-raster approach are formulated upon different domains of objects, with the more verbose digital Jordan curve approach serving as a subset of the hyper-raster approach with respect to objects which are simple regions in R 2 . This paper revisits the approach of the digital Jordan curve by removing the digital Jordan curve restriction, replacing it with the set of pixels that neighbor an exterior pixel, allowing for a host of different relations in pixel space. This increase in domain results in a set of 62 available 9-intersection matrices, a nearly four-fold increase from the original 16 matrices and demonstrates the novelty of this approach with respect to the egg-yolk relations, a model in R 2 for relations between regions with broad boundaries.

Resolution-Free Accurate DNA Contour Length Estimation from Atomic Force Microscopy Images.

This research presented an accurate and efficient contour length estimation method developed for DNA digital curves acquired from Atomic Force Microscopy (AFM) images. This automation method is calibrated against different AFM resolutions and ideal to be extended to all different kinds of biopolymer samples, encompassing all different sample stiffnesses. The methodology considers the digital curve local geometric relationship, as these digital shape segments and pixel connections represent the actual morphology of the biopolymer sample as it is being imaged from the AFM scanning. In order to incorporate the true local geometry relationship that is embedded in the continuous form of the original sample, one needs to find this geometry counterpart in the digitized image. This counterpart is realized by taking the skeleton backbone of the sample contour and by using these digitized pixels' connection relationship to find its local shape representation. In this research, one uses the 8-connect Freeman Chain Code (CC) to describe the directional connection between DNA image pixels, in order to account for the local shapes of four connected pixels. The result is a novel shape number (SN) system derived from CC, which is a fully automated algorithm that can be applied to DNA samples of any length for accurate estimation, with efficient computational cost. This shape-wise consideration is weighted to modify the local length with great precision, accounting for all the different morphologies of the biopolymer sample, and resulted with accurate length estimation, as the error falls below 0.07%, an order of magnitude improvement compared to previous findings.

Handwritten multilingual word segmentation using polygonal approximation of digital curves for Indian languages

Multilingual Optical Character Recognition (OCR) is difficult to develop as different languages exhibit different writing and structural characteristics and it is very difficult to generalize their segmentation process. Character segmentation plays an important role in developing OCR for handwritten languages. The exactness of character segmentation is the integral factor of OCR. In this paper, we exploit this limitation and propose a approach based on the polygonal approximation of the word, which works on more than one Indian languages. This work depicts the novel approach for script independent character segmentation of handwritten text utilizing basic structural properties of the languages. Digitally straight line segments (DSS) of the word is obtained by applying Polygonal approximation to the word. The segmentation of character is language independent and works considerably with skew words as well. Experiments are carried out with four popular Indian languages, Hindi, Marathi, Punjabi, and Bangla. The average success rate for character segmentation of four languages is 90.07% which is satisfactory compared with other existing methods. We use shadow and cumulative stretch feature set with random forest, support vector machine (SVM), multi-layer perceptron (MLP), and convolutional neural network (CNN) classifiers for character recognition. On experimentation, it is observed that our proposed method provided good accuracy for character segmentation and recognition.

光阱中微粒位置高精度检测技术

Precision sensing and measuring based on optical trap technology is innovation and deepening for application of optical force effect from micro-precise manipulation to precise measurement of physical quantities. Precision measurement of position information of the particle in optical trap is key technology of precise sensing and measuring. The method was put forward, which used digital image processing and curve fitting algorithm to detect particle positions in optical trap. The normalized self-correlation function of particle positions was obtained by digital image correlation, and the quadratic curve fitting was used to the normalized self-correlation function curve by least-square method to realize particle position detection of sub-pixel accuracy. Experiments show that the method described in this paper can effectively suppress the quantization effect of hardware and realize fast and high-precision detection of particle position in optical traps. Compared with the direct correlation method, the detection accuracy can be improved by at least one order of magnitude to 0.03 pixel.

Relation-induced connectedness in the digital plane

We introduce and discuss a connectedness induced by n-ary relations (\(n>1\) an integer) on their underlying sets. In particular, we focus on certain n-ary relations with the induced connectedness allowing for a definition of digital Jordan curves. For every integer \(n>1\), we introduce one such n-ary relation on the digital plane \({\mathbb {Z}}^2\) and prove a digital analogue of the Jordan curve theorem for the induced connectedness. It follows that these n-ary relations may be used as convenient structures on the digital plane for the study of geometric properties of digital images. For \(n=2\), such a structure coincides with the (specialization order of the) Khalimsky topology and, for \(n>2\), it allows for a variety of Jordan curves richer than that provided by the Khalimsky topology.