Text identification in natural scenes has emerged as a major research area in computer vision., with several applications including videoretrieval and quick translation systems. Text identification is difficult in na...
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Text identification in natural scenes has emerged as a major research area in computer vision., with several applications including videoretrieval and quick translation systems. Text identification is difficult in natural scene images due to changes in text size, color, orientation, background, contrast, and resolution. Text detection in complex backgrounds is more important to us. To address this issue, this work provides a detection and verification approach based on You Only Look Once Yolo (YOLO) algorithm. To get more accurate end findings, we use the YOLO-v4-Tiny approach to develop our custom text detection model. To evaluate the system, we constructed a ground verification system. Our method obtained 94.85% precision for experimental data.
Many of the Internet applications such as video conferencing, military imagedatabases, personal online photograph albums and cable television require a fast and efficient way of encrypting images for storage and tran...
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Many of the Internet applications such as video conferencing, military imagedatabases, personal online photograph albums and cable television require a fast and efficient way of encrypting images for storage and transmission. In this paper, discrete logarithms are used for generation of random keys and Number Theoretic Transform (NTT) is used as a transformation technique prior to encryption. The implementation of NTT is simple as it uses arithmetic for real sequences. Encryption and decryption involves the simple and reversible XOR operation of image pixels with the random keys based on discrete logarithms generated independently at the transmitter and receiver. Experimental results with the standard bench mark test images proposed in the USC-SIPI data base confirm the enhanced key sensitivity and strong resistivity of the algorithm against brute force attack and statistical crypt analysis. The computational complexity of the algorithm in terms of number of operations and number of rounds is very small in comparison with the other image encryption algorithms. The randomness of the keys generated has been tested and is found in accordance with the statistical test suite for security requirements of cryptographic modules as recommended by National Institute of Standards and Technology (NIST).
A time series database is a collection of data that are generated in series as time goes on and constitutes a large portion of data stored in computers like stock-price movements, weather data, bio-medical measurement...
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A time series database is a collection of data that are generated in series as time goes on and constitutes a large portion of data stored in computers like stock-price movements, weather data, bio-medical measurements, video data etc., Two time sequences of same length are said to be similar if the Euclidean distance is less or equal to a given threshold. The main issue of similarity search in time series databases is to improve the search performance since time sequences are usually of high dimension. So it is important to reduce the search space for efficient processing of similarity search in large time series databases. Popular techniques for efficient retrieval of time sequences in time series databases are DFT, DWT, SvD, PAA, PCA, APCA etc,. In this paper we explore the feasibility of using vari-DWT and Polar wavelet with a comprehensive analysis of the two methods as matching functions which can improve the search performance in Recent-Biased time series databases. vari-DWT is fast to compute and requires little storage for each sequence, It preserves Euclidean distance and recency and also allows good approximation with a subset of coefficients. But it shows poor performance for locally distributed time series data which are clustered around certain values since it uses averages to reduce the dimensionality of data. Polar wavelet uses polar coordinates which are not affected from averages and so can improve the search performance especially in locally distributed time series databases. Moreover, DWT has the limitation that it works best if the length of time series 2 n otherwise it approximates the signal by adding 0 to the right side of the series to make the length to be 2 n which distorts the original signal. Polar wavelet works with time sequences of any length without distorting the original signal. The effectiveness of vari-DWT and Polar wavelets are evaluated empirically on real weather data and synthetic datasets.
Rural health care center, storage and effective retrieval of medical images or volumetric medical videos is one of the important requirement for Telemedicine application. Most of the medical images or 3D images are in...
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ISBN:
(数字)9781538659953
ISBN:
(纸本)9781538659960
Rural health care center, storage and effective retrieval of medical images or volumetric medical videos is one of the important requirement for Telemedicine application. Most of the medical images or 3D images are in DICOM (Digital Imaging and Communications in Medicine) format. Early compression standard like JPEG2000 was inefficient and unsuitable for this kind of imagery. New HEvC (High Efficiency video Coding) standard consist features like intra prediction, refined coding tool such as 35 prediction modes and ability to divide picture into Coding Unit (CU) to utilize all redundancies like Spatial, Temporal and Stastical. Dynamic Quad tree structure of HEvC provides substantial improvement in coding gain performance but adversely it also effect computational complexity. Here, we analyze the ability of HEvC standard to reduce the bit rate that represents medical image content with desired perceptual quality. In this paper, we proposed the dynamic degeneration of CU approach to obtain the improvement in visual quality of medical images with limited bit rate. Quantitative analyses is done by varying the CU block size, which give drastic reduction in bit rate (61.25% on average) with very small change in PSNR (2.01% on average).
With the growing popularity of digital multimedia distributed over broadband channels and networks copyright owners are requesting broadcasted content monitoring to keep their rights. A special need for multimedia mon...
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ISBN:
(纸本)9781424457939
With the growing popularity of digital multimedia distributed over broadband channels and networks copyright owners are requesting broadcasted content monitoring to keep their rights. A special need for multimedia monitoring is coming from advertisement submitters who would like to know how exactly their commercials are broadcasted and which categories of beholders are addressed. The basic unit needed for automated broadcast monitoring and its content evaluation is a robust and fast-enough video matching method. This paper proposes a method that can be used for matching of video streams or fast seeking of a short video sequence in a long video stream. According to real-time run requirements, the developed method is based on the brightness profile processing of significant image regions. Output from the algorithm is a one dimensional time-discretized vector of video sequence fingerprints that contains information about temporal and spatial video content. These fingerprints are appropriate to be stored in databases because of their significantly lower size in comparison to the source video. Having analyzed real video data, we show that reliable video sequence matching using introduced method can be achieved by using a video fingerprint data flow of 32 bytes per second of video stream. According to the robustness of proposed method this rate can be changed. This feature is very important for image processing systems with reduced data transfer bandwidth or low storage capacity, e.g. for the purpose of video-based Tv channels rating measurement.
The future of healthcare delivery systems and telemedical applications will undergo a radical change due to the developments in wearable technologies, medical sensors, mobile computing and communication techniques. Wh...
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ISBN:
(纸本)9781467361491
The future of healthcare delivery systems and telemedical applications will undergo a radical change due to the developments in wearable technologies, medical sensors, mobile computing and communication techniques. When dealing with applications of collecting, sorting and transferring medical data from distant locations for performing remote medical collaborations and diagnosis. E-health was born with the integration of networks and telecommunications. In recent years healthcare systems rely on images acquired in two dimensional domains in the case of still images, or three dimensional domains for volumetric video sequences and images. images are acquired with many modalities including X-ray, magnetic resonance imaging, ultrasound, positron emission tomography, computed axial tomography. Medical informationis either in multidimensional or multi-resolution form, this creates enormous amount of data. retrieval, Efficient storage, management and transmission of this voluminous data are highly complex. One of the solutions to reduce this complex problem is to compress the medical data without any loss (i.e. lossless). Since the diagnostics capabilities are not compromised. This technique combines integer transforms and predictive coding to enhance the performance of lossless compression. The proposed techniques can be evaluated for performance using compression quality measures.
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