The algorithm of spatio-temporal ultrawideband (UWB) signal processing for radiometric imaging is synthesized and investigated. Analytical expressions for the limiting error of the radiometric image estimate and ambig...
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ISBN:
(纸本)9781509010516
The algorithm of spatio-temporal ultrawideband (UWB) signal processing for radiometric imaging is synthesized and investigated. Analytical expressions for the limiting error of the radiometric image estimate and ambiguity function of system are derived. The possibility of ambiguity function formation with one main lobe in the UWB cross-correlation and compensation system with ultra-sparse antenna array is substantiated. The simulation examples of radiometric imaging are shown.
To increase the productivity in agricultural production, speed and accuracy are key requirement. In this paper, we proposed image analysis technique for silkworm egg quality inspection. We focus on silkworm images fro...
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ISBN:
(纸本)9781509006304
To increase the productivity in agricultural production, speed and accuracy are key requirement. In this paper, we proposed image analysis technique for silkworm egg quality inspection. We focus on silkworm images from the last incubation period because it can fully provide statistics of successfully hatched silkworms. Those statistics are useful information for both quantity and quality aspects. The images from the last incubation period contain three different types of egg including shells, defect eggs and unhatched eggs. As a consequence, it is intuitively obvious that the images of last incubation period have higher complexity than the other periods. Our technique use different color images obtained from each incubation period to tackle the problem. We demonstrate a simple method in object detection and classification. The experimental results show that our approach can improvement accuracy for both detection and classification.
Digital era has produced large volume of images which created many challenges in computer science field to store, retrieve and manage images efficiently and effectively. Many techniques and algorithms have been propos...
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ISBN:
(纸本)9781509010264;9781509010257
Digital era has produced large volume of images which created many challenges in computer science field to store, retrieve and manage images efficiently and effectively. Many techniques and algorithms have been proposed by different researcher to implement Content Based image Retrieval (CBIR) systems. This paper discusses performance of different CBIR systems implemented using combined features colour, texture and shape as a prominent feature based on wavelet transform. Choice of the feature extraction technique used in image retrieval determines performance of CBIR systems. In this paper evaluation of performance of three CBIR systems based on wavelet decomposition using threshold, wavelet decomposition using morphology operators and wavelet decomposition using Local Binary Patterns (LBP) is done. Also the performance of these methods is compared with the existing methods SIMPLIcity and FIRM. Average precision is used to compare the performance of the implemented systems. Results indicate that performance of CBIR systems using wavelet decomposition give better results than simplicity and FIRM, also wavelet decomposition with Local Binary Patterns (LBP) exhibit better retrieval efficiency compared to wavelet decomposition using threshold and morphological operators. Theses CBIR systems have been tested on bench mark Wang's image database. Precision versus Recall graphs for each system shows the performance of respective systems.
This paper presents an FPGA based real-time lane detection system for automotive applications. To reduce the computational complexity, the conventional Canny-Hough lane detection algorithm is modified for achieving th...
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ISBN:
(纸本)9781509015719
This paper presents an FPGA based real-time lane detection system for automotive applications. To reduce the computational complexity, the conventional Canny-Hough lane detection algorithm is modified for achieving the real-time processing. The prototype design is realized by using the commercialized FPGA platform and the processing rate is enhanced by 41% compared to the previous detection algorithm.
We introduce a new machine learning approach for image segmentation that uses a neural network to model the conditional energy of a segmentation given an image. Our approach, combinatorial energy learning for image se...
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ISBN:
(纸本)9781510838819
We introduce a new machine learning approach for image segmentation that uses a neural network to model the conditional energy of a segmentation given an image. Our approach, combinatorial energy learning for image segmentation (CELIS) places a particular emphasis on modeling the inherent combinatorial nature of dense image segmentation problems. We propose efficient algorithms for learning deep neural networks to model the energy function, and for local optimization of this energy in the space of supervoxel agglomerations. We extensively evaluate our method on a publicly available 3-D microscopy dataset with 25 billion voxels of ground truth data. On an 11 billion voxel test set, we find that our method improves volumetric reconstruction accuracy by more than 20% as compared to two state-of-the-art baseline methods: graph-based segmentation of the output of a 3-D convolutional neural network trained to predict boundaries, as well as a random forest classifier trained to agglomerate supervoxels that were generated by a 3-D convolutional neural network.
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)9781509018987
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.
The way how we interact with banknotes is changing. This raises questions on how we interact with electronic payment systems. The general idea is to design low-cost electronics for cash handling systems. We establish ...
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ISBN:
(纸本)9781509013159
The way how we interact with banknotes is changing. This raises questions on how we interact with electronic payment systems. The general idea is to design low-cost electronics for cash handling systems. We establish a prototypical demonstrator which allows a consistent image capture quality and is able to handle complex algorithms for banknote authentication on cost-effective hardware. Therefore, tasks regarding reducing the evaluation time, without diminishing the reliability of the algorithms have to be considered. In this contribution we focus on the re-design of an authentication module for detection of commercial offset printing. This module analyses images in view to periodic printing patterns by means of the Discrete Fourier Transform (DFT). We propose to implement two concepts: an adaptive software architecture for DFT and parallel imageprocessing. The re-design reduces evaluation time, without compromising the reliability of the authentication algorithm.
This REU project estimates the reference wave intensity needed by two-step-only quadrature phase shifting holography for 3D object recording and reconstruction, and implements digital holographic image reconstruction ...
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ISBN:
(纸本)9781509015412
This REU project estimates the reference wave intensity needed by two-step-only quadrature phase shifting holography for 3D object recording and reconstruction, and implements digital holographic image reconstruction algorithms on a GPU to meet the real-time processing requirement. The performance on various image sizes is measured and compared between GPU-based and CPU-based implementations. The results show that using GPU to accelerate two-step-only quadrature phase-shifting digital holography can provide significant speedup.
Resolution of goniometric systems on the basis of antenna arrays can be increased due to the secondary digital processing of the accepted signals. Necessary algorithms are created on the basis of solution to inverse p...
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ISBN:
(纸本)9781509025039
Resolution of goniometric systems on the basis of antenna arrays can be increased due to the secondary digital processing of the accepted signals. Necessary algorithms are created on the basis of solution to inverse problems.
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