Thai Sign Language Image Recognition for the Hearing-Impaired using Radial Inverse Force Histogram combined with Max-Min Boundary

Sign language image recognition is also a very interesting research topic. Because it can be applied to help normal people understand and use it as a communication tool for the hearing impaired. The objectives of this research were to: 1) study and analyze Thai Sign Language image recognition image data for hearing impaired, 2) develop Thai Sign Language image recognition system for hearing impaired by using new techniques, and 3) measure the efficiency of Thai sign language image recognition for hearing impaired using Radial Inverse Force Histogram and the Maximum and Minimum boundary values. The results of the research were as follows: 1) The study and analysis of image data of Thai Sign Language Image Recognition In this research, 62,694 sign language images were used, divided into 2 parts: 1) American Sign Language images, which consisted of 36 groups of images, namely 26 groups of letters (AZ) and 10 groups of numbers (0-9), and Part 2) Picture of Thai Sign Language consisting of 61 groups of images, including 44 groups of letters (ก-ฮ), 7 groups of vowels and 10 groups of numbers (0-9). Each group of pictures is rotated, enlarged, and Image promotion There were 6 sub-groups of images in various forms, divided into 2 parts: 70% of the images for training and 30% of the images for testing. 3) The results of measuring the efficiency of image recognition. It is divided into two parts: American Sign Language Image Recognition and Thai Sign Language Image Recognition. Compared with the Angular histogram method, the mean image accuracy was 0.86, the recall of the mean American sign language was 0.91, and the accuracy of the Thai Sign Language was 0.78. The recognition performance for Thai Sign Language images averaged 0.89, while the recognition efficiency was achieved when using radial inverse force histograms in combination with image similarity measurements with maximum-minimum boundary values. Accuracy for Mean American Sign Language was 0.99 and Remembrance for Mean American Sign was 1.00, while Accuracy for Mean Thai Sign Language was 0.89. Mean Remembrance for Thai Sign Language was 0.96. The results of the visual recognition performance measurement of both the American Sign Language and the Thai Sign Language images were very good compared to the Angular Histogram method.

Image Segmentation Using the EM/MPM Algorithm

In this article we propose to place our work in a Markovian framework for unsupervised image segmentation. We give one of the procedures for estimating the parameters of a Markov field, we limit the work to the EM estimation method and the Posterior Marginal Maximization (MPM) segmentation method. Estimating the number of regions who compones the image is relatively difficult, we try to solve this problem by the K-means Histogram method.

Design and Analysis of Imaging Chip Using High-Speed AXI-Interface for MPSOC Applications on FPGA Platform

The recent innovations in real-time video and image enhancements are allowing much advancement in a wide range of diverse applications. These innovations and advancements provide a new hardware architecture which aims to improve the image visualization, processing speed, and complexity reduction in hardware. The imaging chip concept is introduced in this article to support the Multiprocessing system on chip (MPSoC) applications in real-time scenarios on a single chip. The imaging chip model is designed using high-speed interface protocol, which includes different image enhancement algorithms acts as a master model, Advanced Extensible Interface (AXI)-4 as an interface model, and dual-port memory as a slave model. The image enhancement algorithm includes mainly, Brightness control, contrast stretching, Adaptive median filtering (AMF), Edge-detection techniques, image Thresholding, and Image Histogram method. The AXI-4 provides a high-speed interface for communicating master and slave modules. The proposed model work based on the modes of the operation to process the enhanced image output in MPSoC. The design supports multiple masters and multiple slave modules with reconfigurable nature. The imaging chip is a module on the Xilinx ISE environment and implemented on Artix-7 FPGA, along with the performance metrics like chip Area, time, power, and memory utilization are analyzed with improvements. The model offers low latency and high throughput architecture for real-time Multimedia applications.

Research on the Performance of Impressionist Painting Color Visual Communication Based on Wireless Communication and Machine Vision

In order to solve the problem of poor visual communication effect of impressionist painting colors and low accuracy of painting color enhancement by existing methods, this thesis proposes a research on the performance of impressionist painting color visual communication based on machine vision under the background of wireless network. This method can improve the vision, speed, and efficiency of communication, through the analysis of the characteristics of impressionist paintings, and determine the visual communication objects of impressionist painting colors. The process of visual communication is analyzed, and the color matching of impressionist painting is completed with the help of BP neural network algorithm. On this basis, the histogram method is used to process the image brightness of impressionist paintings, the image interpolation method is used to process the image brightness of impressionist paintings, and the image is corrected by gamma correction to complete the image performance research. The color vision communication of impressionist painting needs to correct the gray scale error of impressionist painting and enhance the color of impressionist painting. The experimental results show that the accuracy of this method for the color matching of impressionist painting images is about 98%, which has a certain degree of credibility.

Comparative analysis of the geometrized histogram method and the neural network method for road markings recognition

This paper compares two approaches to determining road markings from video sequences, namely, the method of finding the markings using geometrized histograms and the method based on neural networks. An independent open dataset TuSimple is used to conduct a comparative analysis of the algorithms. Since the investigated methods have different architectures, their work is evaluated according to the following metrics: Accuracy, speed (relative FPS), general computational complexity of the algorithm (TFlops).

Histogram Method for Determining the Location of the Internal Dump in Coal Open Pits

With the deepening of open pit mining, the volume of worked out space increases and, along with it, the potential capacity for storing overburden. At the same time, the pits completely allocated for the internal dumps are used only by the end of the period of the open pit operation. The known theoretical approaches to determining the location of the internal dump are little implemented in the practice of surface mining, which is explained by two reasons. First, standard design solutions are based on wellknown theoretical provisions; secondly, a formalized template approach to substantiating certain design developments in the field of dumping of internal dumps prevails, which pushes them towards their fragmentary rather than integrated implementation. With regard to the conditions of the Kuzbass open-pit mines, the article proposes a modernized interpretation for the formation of structural schemes of the sequence of quarry fields on the basis of constructive-and-parametric studies of a multivariate adaptation of the internal dumping mode.

Влияние магнитного поля на фазовые переходы в модели Гейзенберга на треугольной решетке

The Monte Carlo method was used to study phase transitions, magnetic and thermodynamic properties of the three-dimensional antiferromagnetic Heisenberg model on a layered triangular lattice in a magnetic field. The studies were carried out in the range of variation of the magnetic field value 0≤h≤12. The magnetic structures of the ground state are obtained in a wide range of magnetic field values. The character of phase transitions is determined on the basis of the histogram method of data analysis. It was found that in the range 0≤h≤10, a first-order phase transition is realized. It is shown that a further increase in the magnetic field value removes the degeneracy of the ground state and smears out the phase transition.