One of the most important applications of SAR Earth Observation systems is related to interferometric products (e.g. generation of topographic information of the sensed area, change detection, etc.). Due to specific s...
One of the most important applications of SAR Earth Observation systems is related to interferometric products (e.g. generation of topographic information of the sensed area, change detection, etc.). Due to specific satellite pointing performance in some cases the interferometric applications can be limited. Thanks to the "Frequency Adapter for Interferometric Applications" innovative processing, presented in this paper, it will be possible to increase the interferometric performance. Current processingalgorithms use a single processing centroid for both focusing and radiometric equalization (i.e. for the whitening filter) and are based on the hypothesis that this processing centroid must be the same one of the physical acquisition. According to the FADI technique, two distinct Doppler centroids are envisaged. If the same Doppler centroid is used to focus two images (master and slave, or a series of N images), the term causing decorrelation is cancelled out and the two images preserve coherence. On the other hand, for the equalization of the radiometric pattern, the different Doppler centroid values estimated in each original image should be used. The novel technology offers the possibility of obtaining radiometrically corrected images with maximum spectral overlap, and thus with maximum coherence. The technique is applicable to any SAR mode, and in particular to burst mode (e.g. Ping-Pong and ScanSAR).
Background extraction is a fundamental task present in most computer vision applications such as video surveillance, optical motion capture or multimedia applications. In this paper we explore a particular foreground ...
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ISBN:
(纸本)9781509049912
Background extraction is a fundamental task present in most computer vision applications such as video surveillance, optical motion capture or multimedia applications. In this paper we explore a particular foreground segmentation method based on the well-known Pixel-based Adaptive Segmenter (PBAS) algorithm, proposing modifications that will ease the hardware implementation. Also, the figures of merit of a focalplane approach for foreground segmentation are studied through the impact of typical temporal and spatial noise sources present in the processing elements of smart image sensors such as leakage currents from analog memories or fixed pattern noise (FPN) from mismatch.
images data may contain low resolution characters, and it is not easy to estimate the given low resolution characters. This paper proposed the stochastic model of the low resolution characters and considered the topol...
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ISBN:
(纸本)9781509049172
images data may contain low resolution characters, and it is not easy to estimate the given low resolution characters. This paper proposed the stochastic model of the low resolution characters and considered the topological properties from the color strength of gray scale image.
This paper presents a new method for the segmentation of glandular cavity. Our method is based on the K-means and mathematical morphology. We have segmented the entire glandular cavity and eliminated many of the inter...
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ISBN:
(纸本)9781538611074
This paper presents a new method for the segmentation of glandular cavity. Our method is based on the K-means and mathematical morphology. We have segmented the entire glandular cavity and eliminated many of the interference factors in the gastric glandular image. An important characteristic of our method is that we combined the K-means with the mathematical morphological processing, and carried out the iterative execution which resulted in a gradual refinement, and the algorithm can run in nearly a linear time. images that are processed using our methods can be more effective in helping doctors diagnose disease.
Decreasing profit margins and increasing concerns about animal welfare are boosting the interest for the development of monitoring and analysis technologies specifically targeting the poultry meat production process. ...
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ISBN:
(纸本)9781538611272
Decreasing profit margins and increasing concerns about animal welfare are boosting the interest for the development of monitoring and analysis technologies specifically targeting the poultry meat production process. In this context, this paper addresses monitoring of poultry activity in breeding farms. Specifically, it analyzes the suitability of different vision systems and imageprocessingalgorithms with this purpose. These systems and algorithms have been tested in an actual farm during a breeding cycle. Experimental results are presented demonstrating that density-based computations provide the best results, and that they can be carried out using either video or thermographic images, but the latter are a better option because of practical operating reasons related to varying, low light intensity conditions.
The present work is devoted to the analysis of local objects on radar images. In comparison, the following algorithms are used: decision tree;Bayesian classifier for normal distribution;Nearest neighbor method;Support...
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The present work is devoted to the analysis of local objects on radar images. In comparison, the following algorithms are used: decision tree;Bayesian classifier for normal distribution;Nearest neighbor method;Support Vector Method (SVM). As preliminary processing of images provided by a synthetic aperture radar. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.
作者：
B NalepaA GwiazdaSilesian University of Technology
Faculty Mechanical Engineering Institute of Engineering Processes Automation and Integrated Manufacturing Systems Konarskiego 18A 44 – 100 Gliwice Poland
The article presents an alternative Spearman's rank correlation pattern as an innovative method in detecting the edges of an image by defining characteristic points of the image. Edge detection methods can be coun...
The article presents an alternative Spearman's rank correlation pattern as an innovative method in detecting the edges of an image by defining characteristic points of the image. Edge detection methods can be counted as the imageprocessing stage following the implementation of the 'initial' imageprocessing, which includes: use of filters such as low-pass or high-pass, wavelet transform, etc. In this article hitherto known edge detection algorithms will be replaced with image ranking method. The first chapter of this work contains an analysis of the current knowledge on the ranking of the image. The operation of the Spearman rho algorithm together with its various configurations and the comparison of the two methods studied are presented in turn. Next, the modification of the Spearman rho pattern is presented along with the justification for the use of such a transformation. The same chapter also presents the effects of the algorithm, comparing it with known image ranking methods. The next stage of works consisted in developing a method for the interpretation of the results obtained. In the last chapter of the work, the obtained test results were summarized and analysed.
Recent biometric research has examined the possibility of obtaining attributes such as hair color, age, gender, weight, ethnicity, height, etc. from biometric traits, face, hand geometry, fingerprints and iris. This p...
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ISBN:
(纸本)9781538619599
Recent biometric research has examined the possibility of obtaining attributes such as hair color, age, gender, weight, ethnicity, height, etc. from biometric traits, face, hand geometry, fingerprints and iris. This paper examines detailed study about different process, for each step of predicting gender from iris for achieving better accuracy and authentication. Capturing the iris image in high quality specification camera is used to achieving specific features of iris. Different algorithms and software systems are used to locate the boundaries of an iris image. Mutual Information(MI) is better used to compare other feature in geometry, texture etc. UND_V and GFI datasets are used to get more accuracy in SVM classifier for better gender prediction.
We show that dispersive propagation of light has properties that can be exploited for extracting features from the waveforms. This discovery is spearheading development of a new class of digital algorithms for feature...
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ISBN:
(纸本)9789897582233
We show that dispersive propagation of light has properties that can be exploited for extracting features from the waveforms. This discovery is spearheading development of a new class of digital algorithms for feature extraction from digital images with unique and superior properties compared to conventional algorithms. In certain cases, these algorithms have the potential to be an energy efficient and scalable substitute to synthetically fashioned computational techniques in practice today.
Textual grounding is an important but challenging task for human-computer interaction, robotics and knowledge mining. Existing algorithms generally formulate the task as selection from a set of bounding box proposals ...
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Textual grounding is an important but challenging task for human-computer interaction, robotics and knowledge mining. Existing algorithms generally formulate the task as selection from a set of bounding box proposals obtained from deep net based systems. In this work, we demonstrate that we can cast the problem of textual grounding into a unified framework that permits efficient search over all possible bounding boxes. Hence, the method is able to consider significantly more proposals and doesn't rely on a successful first stage hypothesizing bounding box proposals. Beyond, we demonstrate that the trained parameters of our model can be used as word-embeddings which capture spatial-image relationships and provide interpretability. Lastly, at the time of submission, our approach outperformed the current state-of-the-art methods on the Flickr 30k Entities and the ReferItGame dataset by 3.08% and 7.77% respectively.
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