Contemporary sensor-based robotic systems tend to use an ad-hoc combination of off-the-shelf components for onboard computational needs. The number and type of sensors present, the number and organization of the onboa...
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ISBN:
(纸本)9781509064472
Contemporary sensor-based robotic systems tend to use an ad-hoc combination of off-the-shelf components for onboard computational needs. The number and type of sensors present, the number and organization of the onboard processors, and the algorithms utilized for processing high bandwidth real-time sensor data present researchers and designers with a wide range of choices for which they are currently ill-equipped to evaluate the best options. We present a co-simulation framework for sensor-based mobile robots that allows for the power and performance analysis of custom embedded computing platforms for mobile robots with a range of onboard sensors. We demonstrate the utility of our co-simulation framework by analyzing the power and performance tradeoffs for the computational subsystem of a quadrotor unmanned aerial vehicle (UAV) with onboard camera sensor performing imageprocessing tasks while operating in a custom virtual testbed.
The development in computing power highlights some forgotten algorithms, which were neglected because of their complexity and slowness on early computers. One example is the Wavelet-Transformation Profilometry (WTP) o...
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ISBN:
(纸本)9781509012169
The development in computing power highlights some forgotten algorithms, which were neglected because of their complexity and slowness on early computers. One example is the Wavelet-Transformation Profilometry (WTP) of which successful application is demonstrated in the paper. WTP is a high level signal processing method using orthogonal algorithms for huge datasets. The high performance in quality and running speed makes the described method suitable for medical imageprocessing applications.
In this paper an original approach is presented for real-time detection of user's face position and orientation based only on depth channel from a Microsoft Kinect sensor which can be used in facial analysis on sc...
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ISBN:
(纸本)9783319238142;9783319238135
In this paper an original approach is presented for real-time detection of user's face position and orientation based only on depth channel from a Microsoft Kinect sensor which can be used in facial analysis on scenes with poor lighting conditions where traditional algorithms based on optical channel may have failed. Thus the proposed approach can support, or even replace, algorithms based on optical channel or based on skeleton or face tracking information. The accuracy of proposed algorithms is 91% and was verified on Facial Expressions and Emotions Database using 169 recordings of 25 persons. As the processing time is below 20 ms per frame on a standard PC, the proposed algorithms can be used in real-life applications. The presented algorithms were validated in a prototype application for user emotion recognition based on depth channel information only.
A new 3D transform video coding algorithm is introduced, which does not use motion compensation. More independent and highly efficient algorithms are employed for each key step of the transform coding. For the transfo...
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A new 3D transform video coding algorithm is introduced, which does not use motion compensation. More independent and highly efficient algorithms are employed for each key step of the transform coding. For the transform step, the SCWP (Spectral Condensed Wavelet Packet) is adopted. For the quantization step, a trimming process is implemented, which keeps the bit allocation function of the significant propagation technique but is independent from the entropy coding step. For the entropy coding step, a novel entropy coding technique based upon binary run-length coding is proposed. This binary entropy coding can be applied to multiple symbol source coding, and it approaches an optimal efficiency bound which is within 1.5% of the source entropy when the source approaches iid. Principally, the complexity of the proposed transform video coding algorithm is comparable to that of a 2D still image transform coding algorithm. However, its compression performance is competitive to HEVC at high compression bitrates.
Consistently, the classical image enlargement algorithm is a scientific analytical method for producing a better refined resolution image that is frequently required for advanced digital imageprocessing (DIP) from a ...
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ISBN:
(纸本)9781509048106
Consistently, the classical image enlargement algorithm is a scientific analytical method for producing a better refined resolution image that is frequently required for advanced digital imageprocessing (DIP) from a single lower resolution image that is frequently acquired from digital camera embedded system. Because of its less computation calculation, the Single-image Super-Resolution (SISR) that analytically applied for a single lower resolution image is one of the worldwide effective Super Resolution-Reconstruction (SRR) algorithms thus this paper proposes the image enlargement based on the SISR algorithm using high spectrum estimation and Tukey's Biweight constrain function. In general, the performance of this SISR algorithm is hinge on up to three parameters (b, h, k) however there are burdensome for determining these optimized values for these parameters (b, h, k). In order to solve this problem, the Tukey's Biweight constrain function, which is hinge on merely single parameter (T), contrary to three parameters like the classical constrain function, is engaged in the SISR algorithm. By examining on 14 benchmark images, which are profaned by considerable noise forms, in scientific analytical scrutinizing sector, the novel SISR algorithm illustrates that there is efficiently and effortlessly in parameter setting process but the performance of the novel SISR algorithm (with single parameters) is nearly equal to the original SISR (with three parameters). Due to greatly time reduction in the parameter setting process, this novel SISR algorithm is more advisable for real-time applications.
Edge preservation and precise restoration of details and sharp parts of images is an important issue in modern multimedia systems, 3D imaging, medical imaging and laser microscopy. Objective evaluation of image restor...
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ISBN:
(纸本)9781467395557
Edge preservation and precise restoration of details and sharp parts of images is an important issue in modern multimedia systems, 3D imaging, medical imaging and laser microscopy. Objective evaluation of image restoration algorithms in the sense of sharpness is crucial for choice of method to be used. Moreover, automated focus stacking, selective deblurring and other smart restoration methods rely on the proper sharpness measure. In this paper, a novel approach for image sharpness assessment is proposed. The approach is based on local phase coherence (LPC) in the complex wavelet domain. Using maximum pooling of eight LPC maps in eight spatial directions around each pixel, an image sharpness map is generated. Least absolute deviation criterion applied on sorted non-zero elements of the sharpness map results in the proposed global image sharpness measure. The proposed measure is better suited for applications, in comparison with competitive measures.
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.
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