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Advancing RFID Technology for Virtual boundary detection

IEEE TRANSACTIONS ON MOBILE COMPUTING 2025年第4期24卷 3407-3422页

作者： Li, Xiaoyu Liu, Jia Lin, Zihao Liu, Xuan Wang, Yanyan Zhang, Shigeng Ye, Baoliu Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Peoples R China Hohai Univ Coll Comp & Informat Nanjing 210024 Peoples R China Cent South Univ Sch Comp Sci & Engn Sci & Technol Parallel & Distributed Proc Lab PDL Changsha 410017 Peoples R China

A boundary is a physical or virtual line that marks the edge or limit of a specific region, which has been widely used in many applications, such as autonomous driving, virtual wall, and robotic lawn mowers. However, none of existing work can well balance the deployability and the scalability of a boundary. In this paper, we propose a brand new RFID-based virtual boundary scheme together with its detection algorithm called RF-boundary, which has the competitive advantages of being battery-free and easy-to-maintain. We develop two technologies of phase gradient and dual-antenna AoA to address the key challenges posed by RF-boundary, in terms of lack of calibration information and multi-edge interference. Besides, we consider the presence of multipath in the real world applications, model the effect on signals in the dynamic scenarios, and demonstrate the robustness of our phase gradient-based scheme under multipath. We implement a prototype of RF-boundary with commercial RFID systems and a mobile robot. Extensive experiments verify the feasibility as well as the good performance of RF-boundary, with a mean detection error of only 8.6 cm.

关键词： Image edge detection Robots Radiofrequency identification Calibration Mobile computing Radio frequency Robot sensing systems Location awareness Interference Wire boundary detection Internet of Things RFID virtual boundary

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Clustering Algorithm by boundary detection Base on Entropy of KNN

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IEEE ACCESS 2025年 13卷 62353-62366页

作者： Ding, Jiaman Yin, Jinyuan Jia, Lianyin Fu, Xiaodong Wang, Hongbin Kunming Univ Sci & Technol Fac Informat Engn & Automat Kunming 650500 Peoples R China Kunming Univ Sci & Technol Artificial Intelligence Key Lab Yunnan Prov Kunming 650500 Peoples R China

Clustering analysis has been widely applied in various fields, and boundary detection based clustering algorithms have shown effective performance. In this work, we propose a clustering algorithm by boundary detection based on entropy of KNN (CBDEK). A border point contains only the nearest neighbors within a specific directional range. Thus, we define entropy of KNN (EK) to accurately identify the boundary of the cluster. Since entropy has the property of measuring uncertainty, it can be used to quantify the possibility that a point is a border point. A lower EK indicates an uneven neighbor distribution, increasing the possibility of the point being a border point. Then, the border points are clustered based on the directional similarity of their nearest neighbors. Specifically, if a border point is a neighbor of another border point and most of their nearest neighbors show directional similarity, they are considered to belong to the same cluster. Furthermore, we assign the label of a border point to the interior points located within the maximum nearest neighbor sub-block of this border point to facilitate an efficient allocation for the remaining points (interior points). In addition, our algorithm incorporates noise mitigation techniques using average distance and box plot analysis. The effectiveness of CBDEK is proven by a comparative evaluation of nine algorithms on 24 datasets.

关键词： Clustering algorithms Nearest neighbor methods Entropy Noise Object recognition Shape Vectors Prevention and mitigation Noise measurement Uncertainty boundary detection box plot clustering directional similarity entropy of KNN

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boundary detection IN SKIN TUMOR IMAGES - AN OVERALL APPROACH AND A RADIAL SEARCH ALGORITHM

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PATTERN RECOGNITION 1990年第11期23卷 1235-1247页

作者： GOLSTON, JE MOSS, RH STOECKER, WV UNIV MISSOURI DEPT ELECT ENGN ROLLA MO 65401 USA STOECTER MOSS & CO MED VIS SYST ROLLA MO 65401 USA UNIV MISSOURI DEPT COMP SCI ROLLA MO 65401 USA UNIV MISSOURI HLTH SCI CTR DEPT DERMATOL COLUMBIA MO 65201 USA

Although computerized boundary detection has been studied in depth, current general algorithms are not highly successful when applied to in vivo medical images where the borders are often not clearly defined and are sometimes difficult even for the human eye to detect. In these cases, domain-specific algorithms are necessary to achieve the required accuracy. This paper addresses the problem of automatic detection of tumor borders in digitized images of skin tumors. The complexity of boundary detection in this domain is such that algorithms based on single boundary determinants such as color, luminance, texture, or three-dimensional information are not capable of correctly identifying the boundary in all cases. Hence, an overall approach is discussed that will use confidence levels to combine results from several border detection algorithms based on the individual criteria mentioned. The development of one such algorithm (using a radial search method on luminance informtion)and its results are presented. With this approach, problems such as numerous false borders and unknown shape and size of the tumors are overcome.

关键词： boundary detection Computer vision Edge detection Luminance Melanoma Radial search Skin cancer

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boundary detection in carotid ultrasound images using dynamic programming and a directional Haar-like filter

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COMPUTERS IN BIOLOGY AND MEDICINE 2010年第8期40卷 687-697页

作者： Lee, Yu-Bu Choi, Yoo-Joo Kim, Myoung-Hee Ewha Womans Univ Dept Comp Sci & Engn Seoul South Korea Sungkyunkwan Univ Intelligent Syst Res Ctr Suwon South Korea Korean German Inst Technol Dept New Media Seoul South Korea

The intima-media thickness (IMT) of the carotid artery, obtained from B-mode ultrasound images, has recently been proposed as one of the most useful indices of atherosclerosis and can also be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by time-consuming manual tracing of the interfaces between tissue layers. We propose a computerized method to detect the boundary of the intima-media complex using a directional Haar-like filter that can account for the slope of the boundary in an image. The directional Haar-like filter extracts a directional boundary feature as an image feature in the region of interest, which is used to compute a cost function. A cost function includes not only the directional Haar-like filtering value but also the geometric continuity that is computed for every pixel in the region of interest. The optimal boundary pixels are detected by using a dynamic programming approach that searches for the pixel that minimizes the cost function in each column of the image. We compared the performance of the proposed method with that of manual methods performed by two radiologists. The results showed that our approach produces very similar results to those based on manual tracing, and there was no statistically significant difference between the IMT measurements segmented manually and those analyzed using our method. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Intima-media thickness Directional Haar-like filter Dynamic programming Image feature boundary detection

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boundary detection IN A HEXAGONAL GRID USING ENERGY MINIMIZATION

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PATTERN RECOGNITION LETTERS 1994年第2期15卷 151-159页

作者： CHUN, IG CHO, TI PARK, KH KOREA ADV INST SCI & TECHNOL DEPT ELECT ENGNCOMP ENGN & RES LABTAEJON 305701SOUTH KOREA

In this letter a new boundary detection algorithm for a hexagonal grid is described. We propose a hexagonal boundary label model modified from the square boundary label model defined by Geman et al. (1990) and the penalty patterns reasonable for the hexagonal grid. Because of smaller quantization errors and reasonable penalty patterns, the results of the hexagonal boundary label model are better than those for the square boundary label model.

关键词： IMAGE PROCESSING HEXAGONAL SAMPLING boundary detection EDGE RELAXATION

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boundary detection of optic disk by a modified ASM method

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PATTERN RECOGNITION 2003年第9期36卷 2093-2104页

作者： Li, HQ Chutatape, O Natl Univ Singapore Sch Comp Dept Comp Sci Singapore 117543 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

A new algorithm to automatically detect the boundary of optic disk in color fundus images is proposed. The optic disk is located by principal component analysis (PCA) based model, which is employed to initialize active shape model (ASM) to detect the disk boundary. ASM is modified with two aspects: one is the self-adjusting weight in the transformation from shape space to image space;the other is exclusion of outlying points in obtaining shape parameters. The modifications make the proposed algorithm more robust and converge faster than the original ASM method, especially in the case where the edge of optic disk is weak or occluded by blood vessels. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

关键词： optic disk ASM PCA boundary detection fundus image

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boundary detection using mathematical morphology

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PATTERN RECOGNITION LETTERS 1995年第12期16卷 1277-1286页

作者： Yang, J Li, XB UNIV ALBERTA DEPT COMP SCIEDMONTONAB T6G 2H1CANADA

Object boundaries contain important shape information in an image. Mathematical morphology is shape sensitive and can be used in boundary detection. In this paper, we propose dynamic mathematical morphology which only operates on the parts of interest in an image and reacts to certain characteristics of the region. The next position of the structuring element is dynamically selected at each step of the operation. The technique is used to detect object boundaries and has produced encouraging results.

关键词： shape information boundary detection dynamic mathematical morphology roll dilation

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boundary detection BY CONSTRAINED OPTIMIZATION

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1990年第7期12卷 609-628页

作者： GEMAN, D GEMAN, S GRAFFIGNE, C DONG, P BROWN UNIV DIV APPL MATHPROVIDENCERI 02912 UNIV PARIS 11 EQUIPE STAT APPLF-91405 ORSAYFRANCE

A statistical framework is used for finding boundaries and for partitioning scenes into homogeneous regions. The model is a joint probability distribution for the array of pixel gray levels and an array of labels. In boundary finding, the labels are binary, zero, or one, representing the absence or presence of boundary elements. In partitioning, the label values are generic: two labels are the same when the corresponding scene locations are considered to belong to the same region. The distribution incorporates a measure of disparity between certain spatial features of block pairs of pixel gray levels, using the Kolmogorov-Smirnov nonparametric measures of difference between the distributions of these features. The number of model parameters is minimized by forbidding label configurations, which are assigned probability zero. The maximum a posteriori estimator of boundary placements and partitionings is examined. The forbidden states introduce constraints into the calculation of these configurations. Stochastic relaxation methods are extended to accommodate constrained optimization.

关键词： Constraint optimization Layout Probability distribution Maximum a posteriori estimation Stochastic processes Relaxation methods INSPEC: Controlled Indexing statistical analysis optimisation pattern recognition picture processing INSPEC: Non-Controlled Indexing boundary placements scenes partitioning boundary detection stochastic relaxation constrained optimization probability distribution pixel gray levels scene locations Kolmogorov-Smirnov forbidding label configurations

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boundary detection in echocardiographic images using markovian level set method

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2007年第8期E90D卷 1292-1300页

作者： Cheng, Jierong Foo, Say-Wei Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.

关键词： echocardiographic images segmentation boundary detection MRF level set

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boundary detection by contextual non-linear smoothing

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PATTERN RECOGNITION 2000年第2期33卷 263-280页

作者： Liu, XW Wang, DL Ramirez, JR Ohio State Univ Dept Comp & Informat Sci Columbus OH 43210 USA Ohio State Univ Ctr Cognit Sci Columbus OH 43210 USA Ohio State Univ Ctr Mapping Columbus OH 43212 USA

In this paper we present a two-step boundary detection algorithm. The first step is a nonlinear smoothing algorithm which is based on an orientation-sensitive probability measure. By incorporating geometrical constraints through the coupling structure, we obtain a robust nonlinear smoothing algorithm, where many nonlinear algorithms can be derived as special cases. Even when noise is substantial, the proposed smoothing algorithm can still preserve salient boundaries. Compared with anisotropic diffusion approaches, the proposed nonlinear algorithm not only performs better in preserving boundaries but also has a non-uniform stable state, whereby reliable results are available within a fixed number of iterations independent of images. The second step is simply a Sobel edge detection algorithm without non-maximum suppression and hysteresis tracking. Due to the proposed nonlinear smoothing, salient boundaries are extracted effectively. Experimental results using synthetic and real images are provided. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

关键词： nonlinear smoothing contextual information anisotropic diffusion edge detection boundary detection

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