Due to the intricacy of the process involved in segmenting and extracting the tumor regions in magnetic resonance imaging (MRI), it is quite difficult to successfully detect the diseases. Due to its critical significa...
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With the development of the Industrial Internet of Things (IIoT) and the proposal of smart water conservancy, the integration of the Internet of Things (IoT), edge computing, and computer vision for hydrological infor...
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This paper introduces a 3-D Ground Penetrating Radar imageprocessing System (3DGPRIPS), which reconstructs a 3-D image from a set of subsurface images in 2-D form scanned in a sequence by ground penetration radar (GP...
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ISBN:
(纸本)9781665414517
This paper introduces a 3-D Ground Penetrating Radar imageprocessing System (3DGPRIPS), which reconstructs a 3-D image from a set of subsurface images in 2-D form scanned in a sequence by ground penetration radar (GPR) device and apply various imageprocessing operations developed in the framework of cellular logic array processing. The various 3-D imageprocessing operations developed in the cellular logic array processing framework are: point detection, edge detection, surface detection, thinning, skeletonization and directional textures etc. In the results section performance of Cellular Logic Array processing (CLAP) based edge detection algorithm is compared against Morphological Based Edge detection algorithms.
In today’s digital world, safeguarding data at all times is important, especially with the widespread use of images across various processes. image encryption is vital in concealing sensitive information through cryp...
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ISBN:
(数字)9798350353068
ISBN:
(纸本)9798350353075
In today’s digital world, safeguarding data at all times is important, especially with the widespread use of images across various processes. image encryption is vital in concealing sensitive information through cryptographic techniques, rendering data indecipherable to unauthorized parties. However, existing encryption systems often fall short in terms of both efficiency and security. This research explores chaos theory for image encryption methodologies to address these limitations. A comprehensive study of image encryption fundamentals was conducted, including chaos theory, various chaotic maps, DNA encoding, and encryption system evaluation metrics. Implementation of different chaotic maps such as the logistic map, tent map, and combined logistic-tent map, along with 3D chaotic systems like the Lorenz and Rossler systems, was performed for encryption purposes. Additionally, the 4D extension of the Rossler hyperchaotic system was introduced for enhanced encryption capabilities. Encryption methods were evaluated using metrics such as UACI, NPCR, correlation coefficients, image entropy and histogram analysis, with results compared and tabulated. This research advances image encryption techniques by leveraging chaos theory to achieve heightened security and efficiency in safeguarding image data.
The detection and recognition of targets within imagery and video analysis is vital for military and commercial applications. The development of infrared sensor devices for tactical aviation systemsimagery has increa...
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ISBN:
(纸本)9781510661561;9781510661578
The detection and recognition of targets within imagery and video analysis is vital for military and commercial applications. The development of infrared sensor devices for tactical aviation systemsimagery has increased the performance of target detection. Due to the advancements of infrared sensors capabilities, their use for field operations such as visual operations (visops) or reconnaissance missions that take place in a variety of operational environments have become paramount. Many techniques implemented stretch back to 1970, but were limited due to computational power. The AI industry has recently been able to bridge the gap between traditional signal processing tools and machine learning. Current state of the art target detection and recognition algorithms are too bloated to be applied for on ground or aerial mission reconnaissance. Therefore, this paper proposes Edge IR Vision Transformer (EIR-ViT), a novel algorithm for automatic target detection utilizing infrared images that is lightweight and operates on the edge for easier deployability.
Extractive text summarization stands as a fundamental pursuit within natural language processing, offering the capability to distil extensive textual content while preserving essential information. This research study...
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ISBN:
(数字)9798350379990
ISBN:
(纸本)9798350391558
Extractive text summarization stands as a fundamental pursuit within natural language processing, offering the capability to distil extensive textual content while preserving essential information. This research study presents a Graphical User Interface (GUI) application developed in Python using the TKinter library, designed to streamline the process of document summarization. Leveraging advanced imageprocessing techniques, including face recognition through libraries such as OpenCV and PIL, the proposed system integrates robust security measures for user registration and login functionalities. By utilizing NLP, speed and accuracy, our system offers scalable and adaptable solution for text summarization and language translation with accuracy between 91% to 95%. By employing efficient algorithms, users can extract pivotal sentences from documents, facilitating expedited comprehension and analysis. The fusion of text summarization with secure authentication mechanisms addresses both productivity and security concerns within document management systems, culminating in a professional-grade solution tailored to contemporary information processing needs.
Because of its relevance and complexity in industry, the industrial control terminal collaborative response system is popular among app developers and users, as well as the main target of malevolent criminals. The rap...
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ISBN:
(数字)9798350356656
ISBN:
(纸本)9798350356663
Because of its relevance and complexity in industry, the industrial control terminal collaborative response system is popular among app developers and users, as well as the main target of malevolent criminals. The rapid spread of malware has caused significant harm to users of the industrial control terminal collaborative response system. In this study, we build a model by combining dynamic and static feature detection, compiling test software output information using Fuzz technology, and training with a method that combines dynamic and static interest-based expert recommendation model (DSIERM) algorithm with Bi-LSTM algorithm. Modeling enables specific analysis and classification of test results. Based on this, the TaintBench suite and framework are introduced to compensate for the lack of relevant content for static taint analysis of applications in industrial control terminal collaborative response systems and to increase detection efficiency.
The increase in amount of vehicles in the past few years have made traffic management a difficult job. Technologies play an important role in these systems to regulate the traffic. Number plates are distinguished by t...
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ISBN:
(数字)9798350365092
ISBN:
(纸本)9798350365108
The increase in amount of vehicles in the past few years have made traffic management a difficult job. Technologies play an important role in these systems to regulate the traffic. Number plates are distinguished by their shape, bulk, and color in different countries. Number plates must adhere to rules in India, where a light hue serves as the background and a black color serves as the foreground. This paper recommended a new technique to locate the number plate on a vehicle by using histogram equalization and then identifying the alphabets and digits on the plates using character segmentation using Sobel and Canny edge detection imageprocessing technique.
This paper presents a review on automated disease detection processing. The primary issue in herbal plants is the diagnosis and stratification of its diseases. The conventional process is unpredictable and inconsisten...
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This paper presents a review on automated disease detection processing. The primary issue in herbal plants is the diagnosis and stratification of its diseases. The conventional process is unpredictable and inconsistent, therefore techniques for classifying plants diseases using digital method are necessary as they speed up the identification process. This literature discusses various digital methods for classifying plant diseases. The first step is imageprocessing of herbal plants, which make use of traditional imageprocessing techniques and algorithms to categories diseases in herbal plants based on attributes like texture, color, and shape. The second step is plant categorization based on deep learning and machine learning, such as CNN, KNN, logistic regression etc. Deep learning applications mainly lessen the reliance on designs and preprocessing techniques by joining the entire process. This review provides a basic understanding and knowledge of the current state-of-the-art researches, as well as some dynamic trends for future work.
Multi-object tracking (MOT) is a crucial technique for detecting and tracking multiple objects over time in a scene. It involves locating objects in consecutive frames of a video or sequential observations and establi...
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