Papers by Keyword: Digital Image Processing

Abstract: In digital image processing, artificial intelligence is increasingly applied to image analysis, enhancement, pattern recognition, object recognition, and classification. Unlike traditional image processing, which often relies on rules and predefined algorithms, AI-based approaches use learning, adaptation, and automatic decision-making to identify and manage image features. Key technologies include deep learning, neural networks, and machine learning-based algorithms. AI-driven technology is now present across an expanding range of fields and industries, significantly augmenting classical image processing methods or even replacing certain steps or sub-processes with the power of machine intelligence. The paper aims to highlight the opportunities and trends offered by artificial intelligence in the field of digital image processing.

Abstract: In this paper, a case study is performed for the possibility of using water ethanol mixture in predicting the bubble behavior in multiphase flow. The study compares the concept of formation of foam at the surface of the mixture with the procedure of producing aluminum foam by direct gas injection. Material properties such as kinematic viscosity, density and surface tension on the foaming process will be studied experimentally, while the foam bubble size will be studied by means of digital image processing. Finally the path of the bubble from the nozzle to the liquid surface shall be simulated by means of computational fluid dynamics software and verified experimentally by the usage of a speed camera. Acquirement of this practical knowledge can improve the effectiveness of the real foaming process of the aluminum and aluminum alloys. Simultaneously, it helps to understand main basic features of the formed metal foams. The study is meant to define the best parameters for the foaming process for water-ethanol mixture. Such results are to be compared to their corresponding parameters for the direct injection foaming method for aluminum. The main aim to be able to correlate the 2 processes, in means to decreasing time and cost required to produce aluminum metal foam through test trials, usually causing the waste of material, fuel and energy. Furthermore, the quality and quantity evaluation of the created foam is presented. The effect of the flow rate of the quality of foams can be observed experimentally. The theoretical calculation can reproduce the bubble dynamics observed experimentally.

Abstract: Handmade sketches of different shapes roof structures, often with openings, are outlined on plain sheet of paper. Then, they are transformed by a 2D mesh generation and applied to FEM calculations. Algorithm where only main coordinates of nodes are used as user input data is studied by the Authors. Shape of the surface, its curvature and openings are detected through the procedures developed in the C++ programming language. A particular emphasis is put to the automation of the process. At a present version the method is used for rectangular shapes, which are quite common in civil engineering structures e.g. building elevations. Detection and processing algorithms are implemented with a usage of a library based on a open code called OpenCV. The computer software is described in this paper and some examples are given

Abstract: Therein algorithms of application of digital models for evaluation of porosity and fractional composition of coals based on analysis of their optical images are offered. The models allow allocating significant informational objects and estimation of structural and filtration properties of coals. The results of algorithms application on recognition of the optical images of coals are presented, the particle size distribution of coal charge and porosity of coal is defined.

Abstract: With the increase of requirement for the quality of raw materials in industry, surface defect inspection of steel bar has been an essential part of industrial production. The characteristics of vision-based detection technology for steel bar surface defect and the newest research development were introduced. The working principle of vision inspection technology and key issues were analyzed. Finally, the current domestic research emphases and development trends were proposed.

Abstract: The system in the paper based on Matlab platform. With the aid of image processing toolbox of soil image analysis and processing, the soil grain size distribution and its inclination angle can be got. It overcomes the insufficiency of the existing image edge extraction method, and proposes a new type of detection method, in order that the region of interest can be more accurately extract. The system is helpful to predict the possibility of the regional landslides.

Abstract: This paper can be used as acar key toothed recognition and detection technology and computer vision, imageprocessing technology combined with interdisciplinary applications. Car lockassembly complicated procedures, identification and car keys tooth detection isone of the key aspects of automotive lock assembly, lock a direct impact on theefficiency of the assembly process. The system can effectively improve theexisting car key tooth detection technology to reduce the cost of car keystooth detection recognition, while also rapid and accurate identification, sothat the entire lock assembly process much more efficient.

Abstract: This article takes the industrial robot workpiece sorting issue as a background, introduces an embedded machine vision system based on DM642. The system realizes the image preprocessing, feature extraction, image recognition and other work in DSP, and transmits detection results to robot controller through network interface. Experimental results show that the system can effectively solve the problem of sorting regular geometric workpiece, and can meet the requirements of real-time and accuracy in industrial applications.

Abstract: This paper has a brief introduction to a algorithm that can automatically identify the defective cutting region when automatic paper cutter does quality analysis. The algorithm analyzed the characteristics of processed shear mark image,detected defects,found a critical point of defective part ,then a unique regional recognition algorithm was developed based on the basis of the general processing algorithm. The algorithms can pinpoint the region that cutting defects exist according to the coordinates of critical point accurately, improve the efficiency of quality analysis, and also has stated that image processing is available in the regional recognition of automatic paper cutter.

Abstract: The segmentation and localization of the microscopic cell image is studied based on digital image processing. Firstly, the microscopic cell image is preprocessed by means of Median filter to eliminate the noises. Then, according to the comparison experiments, Prewitt operator is selected for the segmentation of the microscopic cell. Finally, localization of the microscopic cell after segmentation is accomplished by the projection method and experiment results verify the effectiveness of the proposed methods.