To increase data security and information privacy, different algorithms are sometimes used to encrypt the data. However, as the algorithms are studied in detail, their effectiveness begins to decline. In this paper a ...
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ISBN:
(纸本)9780986041983
To increase data security and information privacy, different algorithms are sometimes used to encrypt the data. However, as the algorithms are studied in detail, their effectiveness begins to decline. In this paper a new solution is proposed to strengthen the data security: New Scytale algorithm. This approach is based on an old technique improved by the advantages of modern mathematics and information technology: A software application has also been developed for testing this algorithm.
This paper presents the development and enhancement of a subsurface (underwater) linear unmixing algorithm, called LIGU, specially conceived to determine individual contributions to the measured signal of given spectr...
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ISBN:
(纸本)9781785616525
This paper presents the development and enhancement of a subsurface (underwater) linear unmixing algorithm, called LIGU, specially conceived to determine individual contributions to the measured signal of given spectral reflectance of objects at the bottom of coastal shallow waters. This algorithm is part of a Hyperspectral Coastal image Analysis Toolbox (HyCIAT), which is a repository of tools to be used to retrieve information from object embedded in a diffusive and murky medium. This paper discusses mathematical formulations behind the subsurface unmixing algorithm LIGU and presents enhancements made to the algorithm. Finally, quantitative and qualitative results will be presented using a hyperspectral data set from a controlled and well known environment. These results provide noticeable quantitative improvement when compared with the same algorithms without the enhancements.
Estimator algorithms rely on assumed laser stripe image profile to determine its peek with sub-pixel accuracy. They depend on light intensity readings around the peak and are susceptible to noise and saturation. Noise...
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ISBN:
(纸本)9781509018970
Estimator algorithms rely on assumed laser stripe image profile to determine its peek with sub-pixel accuracy. They depend on light intensity readings around the peak and are susceptible to noise and saturation. Noise and stripe intensity models are commonly used to synthesize and feed test data to estimator algorithms in order to evaluate their accuracy and robustness. For real-time 3D scanning applications estimator algorithms are expected to prefer less computationally demanding estimation techniques. Simple and accurate models of empirical noise and laser stripe profile could be used to improve testing and algorithms accuracy. Modular test setup for 3D scanning is utilized to project a laser stripe on the target with patterned surface. Laser stripe image is captured and processed to extract noise and surface pattern interference. Laser power modulation is used to generate series of captures with various stripe intensities. Captures are partitioned, analyzed and presented according to target surface properties and color channels. image noise interfering with sub-pixel peak detection is analyzed and noise model based on empirical data is proposed. Empirical laser stripe images are analyzed and novel simple laser stripe intensity profile model conforming to empirical data is proposed.
Automatic Identification of disease through imageprocessing in biomedical field is the norm of modern era. Ophthalmologists have used several invasive and noninvasive techniques for early detection of disease. OCT is...
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Mammogram images are now increasingly acquired with full-field digital mammography (FFDM) systems in the clinics. Traditionally, the "for-processing" format of FFDM images is used in computer-aided diagnosis...
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ISBN:
(纸本)9781467399616
Mammogram images are now increasingly acquired with full-field digital mammography (FFDM) systems in the clinics. Traditionally, the "for-processing" format of FFDM images is used in computer-aided diagnosis (CAD) of breast cancer. In this study, we investigate the feasibility of using "for-presentation" format of FFDM (which are more readily available) in development of CAD algorithms for microcalcification (MC) lesions. We conduct a quantitative evaluation of both the image features and the detectability of individual MCs on a set of 188 mammograms acquired in both formats. The results demonstrate that there is a high degree of agreement in the image features between the two image formats, and that a slight increase in false-positives in MC detection is observed in for-presentation images.
Handwriting recognition is the most popular area of research which provides major contribution to the trending technology - mobile computing. This paper provides technical details for the implementation of Handwriting...
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Handwriting recognition is the most popular area of research which provides major contribution to the trending technology - mobile computing. This paper provides technical details for the implementation of Handwriting recognition system. The techniques suitable for offline and online handwriting recognition system are also discussed. Some of the pre-processing and classification algorithms like normalization; re-sampling, Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW) are presented in this paper.
In recent years, image encryption has attracted much attention. Particularly, due to large data capacity and high correlation among pixels, chaos-based image encryption algorithms are more suitable to be applied in th...
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ISBN:
(数字)9783662498316
ISBN:
(纸本)9783662498316;9783662498293
In recent years, image encryption has attracted much attention. Particularly, due to large data capacity and high correlation among pixels, chaos-based image encryption algorithms are more suitable to be applied in the digital image encryption. In this paper, we propose a novel chaotic image encryption algorithm, in which novel multiple chaotic systems and efficient self-adaptive model are initially mingled to enhance the security. Different from conventional algorithms, plaintext participates in the generation of cryptograph in a new way, which follows the idea from the perceptron model. The proposed algorithm enlarges the key space, enhances the randomness of the algorithm, and resists the differential attack effectively. Simulation results are demonstrated that proposed algorithm possesses the high security for the main current attacks, which is an excellent candidate for practical applications of image encryption.
The human body exhibits many vital signs, such as heart rate (HR) and respiratory rate (RR) used to assess fitness and health. Vital signs are typically measured by a trained health professional and may be difficult f...
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ISBN:
(纸本)9781509047611;9781509047604
The human body exhibits many vital signs, such as heart rate (HR) and respiratory rate (RR) used to assess fitness and health. Vital signs are typically measured by a trained health professional and may be difficult for individuals to accurately measure at home. Clinic visits are therefore needed with associated burdens of cost and time spent waiting in long queues. The widespread use of smart phones with video capability presents an opportunity to create non-invasive applications for assessment of vital signs. Over the past decade, several researchers have worked on assessing vital signs from video, including HR, RR and other parameters such as anemia and blood oxygen saturation (SpO2). This paper reviews the different image and video processingalgorithms developed for vital signs assessment through non-contact methods, and outline the key remaining challenges in the field which can be used as potential research topics. The CHROM algorithm produces highest accuracy in detecting the signals from rPPG. There are different challenges of handling large database and motion stabilization which is not provided by any algorithm, this is main area of research in rPPG.
Hyperspectral remote sensing is becoming an active research field in the last decades thanks to the availability of efficient machine learning algorithms and also to the ever-increasing computation power. However, the...
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ISBN:
(纸本)9781509061839
Hyperspectral remote sensing is becoming an active research field in the last decades thanks to the availability of efficient machine learning algorithms and also to the ever-increasing computation power. However, there exist application domains (e.g., embedded applications) in which the deployment of this kind of systems becomes unfeasible due to the high requirements related to the size, power consumption or processing speed. A way to overcome this trouble consists on using any method able to scale-down the dimensionality of the problem and/or to reduce the complexity of the machine learning models. In this paper, we propose the use of a multiobjective genetic algorithm to minimize both the dimension of the input space and the size of the machine learning model. In particular, we have developed a hyperspectral image classifier based on an Extreme Learning Machine (ELM) for which the number of system inputs (dimensionality) and the number of hidden neurons are minimized without decreasing its performance. The system is evaluated by using a known benchmark dataset.
This article describes a novel real-time algorithm for the purpose of extracting box-like structures from RGBD image data. In contrast to conventional approaches, the proposed algorithm includes two novel attributes: ...
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ISBN:
(纸本)9781510601086
This article describes a novel real-time algorithm for the purpose of extracting box-like structures from RGBD image data. In contrast to conventional approaches, the proposed algorithm includes two novel attributes: (1) it divides the geometric estimation procedure into subroutines having atomic incremental computational costs, and (2) it uses a generative "Block World" perceptual model that infers both concave and convex box elements from detection of primitive box substructures. The end result is an efficient geometry processing engine suitable for use in real-time embedded systems such as those on an UAVs where it is intended to be an integral component for robotic navigation and mapping applications.
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