The automation project with vision based positioning by using ABB IRB 140 robot is proposed, the coordinate transformation and camera calibration is applied, two types gas leakage test for HP dryers are proposed and t...
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ISBN:
(纸本)9781538676424
The automation project with vision based positioning by using ABB IRB 140 robot is proposed, the coordinate transformation and camera calibration is applied, two types gas leakage test for HP dryers are proposed and the imageprocessingalgorithms for welding points of gas leakage test by dividing three areas of chassis are proposed. For this purpose, the robotic automation system has been installed and the real-time experimental studies are performed to show the effectiveness of the vision based positioning ABB IRB 140 robot for the gas leakage test by presentation the derivations of welding points positions.
image Compression is used to decrease the number of bits required to store and transmit images without any measurable loss of information. The impact of using different lossless compression algorithms on the compressi...
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Medical science has been contributing its active role in fighting vigorously against the life ceasing diseases. The algorithm is proposed by investigating the existing segmentation algorithms in the field of leukemia ...
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ISBN:
(纸本)9781538628430;9781538628423
Medical science has been contributing its active role in fighting vigorously against the life ceasing diseases. The algorithm is proposed by investigating the existing segmentation algorithms in the field of leukemia research for the sake of supporting hematopathologists to recognize Acute Lymphocytic Leukemia (ALL) by analyzing the blood cell images. There are four levels of separating and classifying benign and malignant white blood cells (WBC). They are, preprocessing, segmentation, extraction of features and classification. As a preliminary task of image analysis, segmentation is done with morphological operators and Otsu's thresholding. Then utilization of nucleus features with supervised KNN classifier gains the classification accuracy of 95.96%, 95.92% of sensitivity and 96% of specificity.
Circular Synthetic Aperture Radar (CSAR) can overcome some significant inherent drawbacks of conventional SAR imaging methods such as limited resolution and restricted aspect angle interval of the illuminated scene. I...
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ISBN:
(纸本)9781538616208
Circular Synthetic Aperture Radar (CSAR) can overcome some significant inherent drawbacks of conventional SAR imaging methods such as limited resolution and restricted aspect angle interval of the illuminated scene. In addition, utilizing of different elevation acquisition has the capability to reduce undesired sidelobes of single flight CSAR. Because of the sparse nature of elevation aperture data of multi baseline CSAR, sparse signal processing approaches have been employed instead of typical algorithms, firstly, the number of samples for recording and processing can be reduced significantly by sub-aperture acquisition. Moreover, sparsity driven approaches such as Compressive Sensing (CS) represents considerable sidelobe reduction. Whereas CS demonstrates adequate resolution, reducing the number of tracks degrades the ultimate image abruptly. Consequently, we exploit the novel idea of Distributed Compressive Sensing (DCS) with joint sparsity in this context to improve resolution and reduce sidelobe effect substantially in the consequent full aperture 3D image. Furthermore, implementation of the state-of-the-art sparsity-driven algorithm improve our imaging result and reduce computational burden.
Due to convenient installation, large coverage area and be effective, video detection technology has become a research focus in current traffic incident detection field. This paper simply introduces common tracking al...
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ISBN:
(纸本)9781538680322
Due to convenient installation, large coverage area and be effective, video detection technology has become a research focus in current traffic incident detection field. This paper simply introduces common tracking algorithm and its principle of several moving objects and puts forward a Kalman filter-based feature matching tracking method. First, we apply temporal difference method to detect moving objects and obtain their initial position. Then, this paper adopts Kalman filter to predict the moving objects position at next period and utilizes results of moving objects detection to evaluate and correct predicting results. This obtains correct position of moving objects and analyzes vehicles movement according to tracking results. The experiment results show this method can effectively solve reliable tracking under condition of partial occlusion and short-time total occlusion of moving targets.
In modern information systems, decision making based on imageprocessing is hampered by the impact of negative external and internal factors leading to image blurring, which introduces uncertainty in this process. In ...
In modern information systems, decision making based on imageprocessing is hampered by the impact of negative external and internal factors leading to image blurring, which introduces uncertainty in this process. In this regard, algorithms and models are used to reduce the effect of uncertainty in image analysis. The article presents a new adaptive algorithm for imageprocessing in different wave bands. The article also presents the results of research on the training of operators of imageprocessingsystems in conditions of uncertainty. It is proposed to train the operators of these systems on the basis of a competence-based approach using an information system that allows you to create individual training paths for the operators. The implementation of the training information system is proposed to be made on the basis of a web service.
Acute Lymphoblastic Leukemia (ALL) is the most prevalent acute leukemia in adults after Acute Myeloid Leukemia, with a diffusion of over 6500 persons per year just in the United States. In this research, we propose a ...
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Acute Lymphoblastic Leukemia (ALL) is the most prevalent acute leukemia in adults after Acute Myeloid Leukemia, with a diffusion of over 6500 persons per year just in the United States. In this research, we propose a smart assistant determination method for ALL diagnosis using microscopic images. In this regard, K-means is employed to extract cell images after that wavelet transform is hired on cell images then statistical moments of the transformed image are computed to extract features. Afterward, a Chain Tabu search algorithm is proposed for feature selection of normal and abnormal cells to enable classifiers classifying ALL efficiently. Finally, Multi-Layer Perceptron (MLP) is used for classification. The proposed method is evaluated on ALL-IDB2. The proposed method achieved the accuracy of 98.88% and outperforms existed ALL diagnosis methods.
Currently, a multitude of systems are developed that process a continuous flow of images. They are used, for example, for video surveillance, inspection and control of products manufactured in production lines, automa...
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ISBN:
(纸本)9781538637319
Currently, a multitude of systems are developed that process a continuous flow of images. They are used, for example, for video surveillance, inspection and control of products manufactured in production lines, automatic guidance of robots, vehicles, etc. For these systems to be useful, they must be able to process and store images at a minimum frequency. Therefore, when designing these systems it will be essential to determine the frequency at which they can operate depending on the characteristics of the images, the algorithms used to process them, and the computer hardware selected. Despite the importance of estimating and adjusting the performance of these imaging systems, there are hardly any methodologies for developing the performance engineering of them. With the aim of covering this gap, this article presents a simple experimental method to develop the performance engineering of the imageprocessingsystems and in particular to determine their maximum operational frequency or throughput. Using the proposed method, any performance engineer can determine the maximum working frequency of a system systematically and check that it exceeds the minimum required frequency. In addition, the engineer can also obtain the necessary information to reconfigure the system, eliminate performance bottlenecks, and take advantage of the computing power of the hardware properly.
Research has been done to extract fabric characteristics from its 2D images. Based upon analyzing such characteristics, this paper focuses on automatically identifying and recognizing different clothing fabrics. Throu...
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Research has been done to extract fabric characteristics from its 2D images. Based upon analyzing such characteristics, this paper focuses on automatically identifying and recognizing different clothing fabrics. Through analyzing digital image, its feature extraction system is designed. Clothing fabric folds can be extracted by digital image re-processing. The measurement and calculation depends on the characteristics of the whole folds, which focus on analyzing the differences between fabric folds, then designing the algorithms to identify different clothing fabrics. Based upon analyzing its fold image, clothing fabric information can be extracted to obtain the ratio of length and width, height, and the ratio of area and perimeter. The different fabric types can be classified (classifies) depending upon such parameters. Comparison with these references of the different fabrics shows that such method can be used to represent fabric folds characteristics. By using these indicators to compare the effect of different fabrics, it is found out(We notice) that these indicators can be taken as reflection and description for fabric identification.
This edited volume presents the best chapters presented during the international conference on computer and applications ICCA17 which was held in Dubai, United Arab Emirates in September 2017. Selected chapters presen...
ISBN:
(数字)9783319899145
ISBN:
(纸本)9783319899138
This edited volume presents the best chapters presented during the international conference on computer and applications ICCA17 which was held in Dubai, United Arab Emirates in September 2017. Selected chapters present new advances in digital information, communications and multimedia. Authors from different countries show and discuss their findings, propose new approaches, compare them with the existing ones and include recommendations. They address all applications of computing including (but not limited to) connected health, information security, assistive technology, edutainment and serious games, education, grid computing, transportation, social computing, natural language processing, knowledge extraction and reasoning, Arabic apps, image and pattern processing, virtual reality, cloud computing, haptics, information security, robotics, networks algorithms, web engineering, big data analytics, ontology, constraints satisfaction, cryptography and steganography, Fuzzy logic, soft computing, neural networks, artificial intelligence, biometry and bio-informatics, embedded systems, computer graphics, algorithms and optimization, Internet of things and smart cities. The book can be used by researchers and practitioners to discover the recent trends in computer applications. It opens a new horizon for research discovery works locally and internationally.
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