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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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.
In the event of a maritime disaster, casualties need to be found and rescued promptly. imageprocessing methods could help to perform automated detection from a UAV. The main current approaches make use of multispectr...
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ISBN:
(纸本)9781509044962
In the event of a maritime disaster, casualties need to be found and rescued promptly. imageprocessing methods could help to perform automated detection from a UAV. The main current approaches make use of multispectral and thermal cameras, which can deal with lightning difficulties but are expensive and could suffer from high noise problems. This paper presents a method combining both color analysis and frequency patterns identification using an inexpensive vision camera (EO camera), and implements it through an adaptive algorithm to deal with a dynamically changing background. The method is tested successfully in different environments.
Real-time computing system attracts more and more attention in both academic researches and industrial applications. One of the real-time computing systems, Apache Storm, because of its characteristics of stream proce...
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Real-time computing system attracts more and more attention in both academic researches and industrial applications. One of the real-time computing systems, Apache Storm, because of its characteristics of stream processing and high fault tolerance, is widely used for machine learning and distributed remote process call (RPC), etc. However, the existing approaches to decompose topology for Storm cannot ensure an optimized performance. In this paper, we propose an adaptive topology decomposition algorithm for Storm where topology decomposition based on cluster status and components of topology can be performed at run time. We have evaluated the processing performance and the load balancing of the algorithm. The evaluation results indicate that the proposed algorithm has better performances on task processing and load-balancing than the existing algorithms.
We consider the problem of recovering an image using block compressed sensing (BCS). Traditional BCS algorithms recovers each image block independently and utilizes post-processing methods for removing the blocking ar...
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ISBN:
(纸本)9781538639542
We consider the problem of recovering an image using block compressed sensing (BCS). Traditional BCS algorithms recovers each image block independently and utilizes post-processing methods for removing the blocking artifacts. In contrast, we propose an image recovery method free of post-processing, where we utilize a lapped transform (LT) for the sparse representation of the image in order to reduce the blocking artifacts. Specifically, we derive an iterative image reconstruction method, where a small number of adjacent measurement blocks are jointly processed for recovering an image block. For this purpose, we propose a novel sparse Bayesian learning (SBL) algorithm.
image compression and size reduction increases the number of images stored on a memory space and reduces bandwidth consumption while increasing transmission speed on a communication channel. images can be compressed a...
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ISBN:
(纸本)9781509016457
image compression and size reduction increases the number of images stored on a memory space and reduces bandwidth consumption while increasing transmission speed on a communication channel. images can be compressed and decompressed using different methods and algorithms. With the vast increase of quality and size, dedicated processors with parallel processing blocks such as FPGAs are mainly targeted to implementing faster processing circuits and algorithms. This paper proposes FPGA hardware architecture for a stereoscopic image compression algorithm based on block matching, watermarking and Hamming code.
In conventional sparse representations based dictionary learning algorithms, initial dictionaries are generally assumed to be proper representatives of the system at hand. However, this may not be the case, especially...
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In conventional sparse representations based dictionary learning algorithms, initial dictionaries are generally assumed to be proper representatives of the system at hand. However, this may not be the case, especially in some systems restricted to random initialization. Therefore, a supposedly optimal state-update based on such an improper model might lead to undesired effects that will be conveyed to successive learning iterations. In this paper, we propose a dictionary learning method which includes a general error-correction process that codes the residual left over from a less intensive initial learning attempt and then adjusts the sparse codes accordingly. Experimental observations show that such additional step vastly improves rates of convergence in high-dimensional cases, also results in better converged states in the case of random initialization. Improvements also scale up with more lenient sparsity constraints.
Synthetic aperture radar (SAR) is a widely used technique suited for real-time and all-weather imaging of natural surfaces and artificial objects. To improve image resolution and increase accuracy of radar cross secti...
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Synthetic aperture radar (SAR) is a widely used technique suited for real-time and all-weather imaging of natural surfaces and artificial objects. To improve image resolution and increase accuracy of radar cross section estimation the problem of statistical synthesis of signal processing algorithm in SAR is solved. Proposed method allows to form images with super-resolution in azimuth and range. Synthesis is performed using modern theory of radio engineering systems statistical optimization.
A student-built unmanned aerial system (UAS) was developed by the University of Hawaii Drone Technologies team for the 2017 Association for Unmanned Vehicle systems International (AUVSI) Student Unmanned Aerial System...
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A student-built unmanned aerial system (UAS) was developed by the University of Hawaii Drone Technologies team for the 2017 Association for Unmanned Vehicle systems International (AUVSI) Student Unmanned Aerial System (SUAS) competition, which simulates a search-and-rescue (SAR) mission. The UAS comprises a fixed-wing airframe integrated with flight control and communication components, and is capable of autonomous waypoint navigation, in-flight data transfer, aerial image capture with onboard imageprocessing, and aerial payload delivery. The UAS is capable of executing a 30-minute SAR mission in search of a simulated lost hiker. SAR tasks include autonomously navigating to a designated area, conducting a search for alphanumeric targets over a 370,000-m~2 search area, and autonomously dropping an 8-oz care package to the lost hiker. image-processing and computer-vision algorithms can correctly sense and identify the alphanumeric targets with 75% accuracy.
The article is devoted to solving the fundamental scientific problems of developing universal methods of video sequence processing for the detection and tracking of objects of *** work on the subject,authors designed ...
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The article is devoted to solving the fundamental scientific problems of developing universal methods of video sequence processing for the detection and tracking of objects of *** work on the subject,authors designed new methods and algorithms for universal monitoring systems for wide range of objects in the video sequences which could be implemented at miniaturized data processing *** this paper we describe a new method of search and recognition of point objects on a complex background,a new algorithm for the analysis of the found set of descriptors of local features to filter false positives filter local features,object detection criterion in the image,a new algorithm for the analysis of the trajectory of a point object on the basis of a recursive Kalman filter to predict the trajectory the movement of point objects.
Lack of Proper Information around Sri Lankan Historical Places cause to give false information. If ruins scattered around same place tourists are struggling to identify them. Sometimes there are small sign boards but ...
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Lack of Proper Information around Sri Lankan Historical Places cause to give false information. If ruins scattered around same place tourists are struggling to identify them. Sometimes there are small sign boards but they don't provide enough information. In this paper we address this challenge by using user captured image or search imaged. Our approach is produced a single document about identified places. System identify the places through training dataset using SVM. System will increase the accuracy of prediction by taking GPS data and user inputs necessarily. The evaluation shows that our approach is more accurate than the existing systems.
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