Application of discrete transforms with selective coefficients for blind image watermarking

Lydia, E. Laxmi; Raj, R. Joshua Samuel; Selvam, Rajajee; Elhoseny, Mohamed; Shankar, K.

doi:10.1002/ett.3771

Cited by 28 publications

(17 citation statements)

References 43 publications

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“…When a node in the cluster receives this message, it will send digital at this interval. After the digital transmission period, the cluster head node collects the digital sent from the nodes in the cluster, processes the digital by running digital-intensive algorithms, and sends the results directly to the receiver node [33][34][35].…”

Section: Intracluster Routingmentioning

confidence: 99%

“…e research premise of unconnected effector Internet topology control is to control the power supply and select the corresponding backbone Internet node copper cables to meet the the Internet coverage and connection conditions [35]. Time eliminates those unimportant communication paths in the nodes, enabling it to form a structured and efficient digital transmission network topology.…”

Section: Topological Structure Controlmentioning

confidence: 99%

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Parameter Detection of an On-Chip Embedded Debugging System of Wireless Sensor Internet Based on LEACH Algorithm

Zhou

2021

Mathematical Problems in Engineering

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With the rapid development and maturity of unconnected communication technology, effector technology, embedded computing technology, and distributed information processing technology, as well as the rapid advancement of digital processing and computing capabilities, unconnected effector Internet has received more and more attention. It is a new type of self-organizing unconnected multihop Internet. With the development and progress of technology and society, the development of unconnected effector Internet is also advancing by leaps and bounds, and it has a wide range of applications in many fields such as military, civil, environmental, medical, and industrial. At present, the research on unconnected effector Internet mainly focuses on the communication protocol, but there is almost no research on input review of unconnected effector Internet. Due to the limited energy of the effector and the limitation of the transmission signal bandwidth, the use of limited resources for input review research in effector Internet is of great significance to the development of unconnected effector Internet. Therefore, this paper studies the input review of unconnected effector Internet based on the L-A model on the on-chip embedded tune system. Because the classic low-power adaptive cluster layering protocol (LEACH) has the problems of unbalanced energy consumption and short node life cycle, this paper uses the embedded tune technology based on the L-A model and analyzes the remaining energy and location of the unconnected effector Internet node. Parameters are tested and studied. Through the research on the input review of unconnected effector Internet, the simulation results obtained show that the research in this paper is feasible and reasonable.

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Section: Intracluster Routingmentioning

confidence: 99%

Section: Topological Structure Controlmentioning

confidence: 99%

Parameter Detection of an On-Chip Embedded Debugging System of Wireless Sensor Internet Based on LEACH Algorithm

Zhou

2021

Mathematical Problems in Engineering

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“…It is a model that describes system characteristics related to the timing and sequence of operations, events that affect change, sequence of events, context of events, and organization of events. It is usually expressed as a mathematical equation for a continuous or discrete time variable [10]. e dynamic model of the system can be described by sequence diagram, state diagram, and activity diagram.…”

Section: Dynamic Degreementioning

confidence: 99%

Spatial and Temporal Pattern Analysis of Land Use in Yangtze River Delta Based on Remote Sensing and GIS in Intelligent Environment

Zhan

et al. 2021

Advances in Civil Engineering

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Land use change plays an important role in regional socio-economic development and global environmental change. Whether the land is effectively and efficiently used is not only related to the income level of the people in the surrounding cities but also closely related to the local economy and national economy. Intelligent environment refers to the indoor environment with a variety of data acquisition equipment. Combined with related technologies, the reasoning and analysis of the data can be used to realize the functions of activity identification, data perception, and control. In addition, the Yangtze River Delta is an economically developed area in China, and its land use situation is related to the economic development in the next ten or even decades. Therefore, it is necessary to analyze the spatial and temporal pattern of land use in Yangtze River Delta region by remote sensing image technology and GIS in intelligent environment. Based on intelligent environment, this paper uses RS and GIS technology to interpret remote sensing image and map land use in multitemporal coastal zone. The land use dynamic degree model and spatial interpolation method were used to analyze and evaluate the spatial and temporal evolution characteristics of land use in the Yangtze River Delta region, and the landscape pattern changes in the Yangtze River Delta region were analyzed and evaluated. This study found that the land use types in the Yangtze River Delta have transformed each other, and the land use change speed is fast, which is inseparable from the rapid economic development. In the future, in addition to maintaining the rapid and stable development of industry, the rational use of limited land resources, the improvement of agricultural development short board, and the improvement of tourism economic benefits will make the economy of the Yangtze River Delta region to a new level.

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“…Aiming at the problems of slow training speed of high-dimensional image information input network and low information utilization rate, the feature selection is performed to reduce the image dimension and simplify the image information, and extract useful feature information that can better reflect the essence of the target image, and improve Network recognition rate. Feature extraction is the process of obtaining effective information that reflects the image from the original image information through different function transformations [32]. Methods such as principal component analysis (PCA) and linear discrimination are more common linear transformation methods [33][34].…”

Section: ) Feature Extraction and Selectionmentioning

confidence: 99%

Target Recognition Method of Rehabilitation Robot Based on Image Local Features

Xing

2020

IEEE Access

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Target recognition technology is an important topic in the field of artificial intelligence, which is widely used in fields such as medicine, robot vision, highway traffic, and VR technology. In the robot vision system, the target recognition technology requires high precision, real-time, and practicality, and it must be able to cope with the harsh recognition environment on site. This paper mainly studies the target recognition method of rehabilitation robot based on image local features. In this paper, a rehabilitation robot recognition system is established based on the local features of the image and the target recognition technology. Firstly, after collecting or processing the initially prepared images, feature extraction is performed, and the feature vectors extracted from the features are classified and recognized and then transferred to the recognition model of the rehabilitation robot. Then, according to the functional requirements of the rehabilitation robot recognition system, the "one-to-many" rehabilitation mode and real-time system monitoring are realized to accurately identify the target state. Finally, the Harris algorithm is used to convert the predetermined image set into a grayscale image, and the Gaussian distribution is used uniformly to determine the location and proportion of the feature points, and extract the corresponding image.The Harris matching method used in this article is very effective and has the highest accuracy. The number of correct matches accounted for 58.3%. Compared with the SIFT algorithm and the Harris+SIFT algorithm, the accuracy rate increases by 12.3% and 14.4%, respectively. The recall rate increased by 13.2% and 8.9% respectively. The experimental results show that the target recognition technology of rehabilitation robot based on image local features is more accurate than general technology.

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Application of discrete transforms with selective coefficients for blind image watermarking

Cited by 28 publications

References 43 publications

Parameter Detection of an On-Chip Embedded Debugging System of Wireless Sensor Internet Based on LEACH Algorithm

Parameter Detection of an On-Chip Embedded Debugging System of Wireless Sensor Internet Based on LEACH Algorithm

Spatial and Temporal Pattern Analysis of Land Use in Yangtze River Delta Based on Remote Sensing and GIS in Intelligent Environment

Target Recognition Method of Rehabilitation Robot Based on Image Local Features

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