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segmentation of individual mangrove trees using UAV-based LiDAR data

ECOLOGICAL INFORMATICS 2023年 77卷

作者： You, Haotian Liu, Yao Lei, Peng Qin, Zhigang You, Qixu Guilin Univ Technol Coll Geomat & Geoinformat 12 Jiangan Rd Guilin 541006 Peoples R China Guilin Univ Technol Guangxi Key Lab Spatial Informat & Geomat 12 Jiangan Rd Guilin 541004 Peoples R China Guangxi Vocat Coll Water Resources & Elect Power Dept Hydraul Engn 99 Changgu Rd Nanning 530023 Peoples R China

Accurate assessment of structural parameters is essential to effectively monitor the mangrove resources. However, the extraction results of mangrove structural parameters are closely related to the segmentation results of individual trees. Although the results of individual tree segmentation are influenced by many factors, the specific factors affecting the segmentation results of individual mangrove trees, such as data source, image resolution, segmentation algorithm, and stand density, have not yet been elucidated. Therefore, in this study, canopy height models (CHMs) with different spatial resolutions were derived from unmanned aerial vehicle (UAV)-based light detection and ranging (LiDAR) data. Moreover, the watershed algorithm (WA), regional growth (RG), and improved K-nearest neighbour (KNN) and bird's eye view (BEV) faster region-based convolutional neural network (R-CNN) algorithms were used to segment the individual mangrove trees based on CHMs and LiDAR data at three sites with varying stand densities. Finally, different segmentation algorithms, image resolutions, and forest densities were comparatively assessed to determine their influence on the segmentation results of individual trees. segmentation accuracy of the improved KNN algorithm was the highest among the CHM-based algorithms, such as the WA, RG, and improved KNN algorithms, with an optimal F of 0.893 and minimum F of 0.628. R-CNN algorithm based on LiDAR data had an optimal F value of 0.931 and minimum F value of 0.612. Based on the segmentation results, the overall accuracy ranking of the different segmentation algorithms was BEV Faster R-CNN > improved KNN > RG > WA. The ranking of the segmentation results for sites with different stand densities was low-density (LD) > medium-density (MD) > high-density (HD). For LD and MD sites, the BEV Faster R-CNN algorithm had the highest F values (0.931 and 0.712, respectively). For the HD site, all algorithms performed poorly, and the F values of all alg

关键词： LiDAR data CHM segmentation algorithm Stand density Spatial resolution

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On the Need for Accurate Brushstroke segmentation of Tablet-Acquired Kinematic and Pressure Data: The Case of Unconstrained Tracing

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algorithmS 2024年第3期17卷 128页

作者： Franz, Karly S. Reszetnik, Grace Chau, Tom Holland Bloorview Kids Rehabil Hosp Bloorview Res Inst Toronto ON M4G 1R8 Canada Univ Toronto Inst Biomed Engn Toronto ON M5S 3G9 Canada Univ Toronto Fac Med Toronto ON M5S 1A8 Canada

Brushstroke segmentation algorithms are critical in computer-based analysis of fine motor control via handwriting, drawing, or tracing tasks. Current segmentation approaches typically rely only on one type of feature, either spatial, temporal, kinematic, or pressure. We introduce a segmentation algorithm that leverages both spatiotemporal and pressure features to accurately identify brushstrokes during a tracing task. The algorithm was tested on both a clinical and validation dataset. Using validation trials with incorrectly identified brushstrokes, we evaluated the impact of segmentation errors on commonly derived biomechanical features used in the literature to detect graphomotor pathologies. The algorithm exhibited robust performance on validation and clinical datasets, effectively identifying brushstrokes while simultaneously eliminating spurious, noisy data. Spatial and temporal features were most affected by incorrect segmentation, particularly those related to the distance between brushstrokes and in-air time, which experienced propagated errors of 99% and 95%, respectively. In contrast, kinematic features, such as velocity and acceleration, were minimally affected, with propagated errors between 0 to 12%. The proposed algorithm may help improve brushstroke segmentation in future studies of handwriting, drawing, or tracing tasks. Spatial and temporal features derived from tablet-acquired data should be considered with caution, given their sensitivity to segmentation errors and instrumentation characteristics.

关键词： biomedical signal processing segmentation algorithm biomechanical phenomena error propagation tracing

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Sheep Posture Recognition Based on SVM 2nd

Sheep Posture Recognition Based on SVM

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2nd International Conference on Advanced Intelligent Technologies (ICAIT)

作者： Yao, YaJuan Tan, Han Yao, Juan Zhang, Cheng Tian, Fang Huazhong Agr Univ Coll Informat Wuhan Hubei Peoples R China Wuhan Vocat Coll Software & Engn Coll Mech Engn Wuhan Hubei Peoples R China

ISBN: (纸本)9789811697357;9789811697340

The evaluation of body size parameters and morphology based on body size parameters can reflect the growth and development characteristics, production performance and genetic characteristics of sheep. Therefore, studying the measurement of body size parameters and morphological evaluation is an effective way to determine the reasonable breeding of sheep farms and improve the breeding efficiency. In the measurement of human body size based on machine vision, the change of posture has a great influence on the human body size parameters. In this paper, a segmentation algorithm of sheep head, body and legs based on the sheep contour is proposed. Through this algorithm, five posture features are extracted, which are the angle between the hip point and the lower right corner coordinate of the head, the angle between the hip point and the lower left corner coordinate of the head, the angle between the lower right corner coordinate of the body and the lower right corner coordinate of the head, the angle between the lower right corner coordinate of the body and the upper left corner coordinate of the head and the length-width ratio of the circumscribed rectangle. The test results show that the accuracy of the program compiled by the hierarchical vector machine algorithm reaches 95.68%.

关键词： Hierarchical vector machine algorithm segmentation algorithm Sheep posture recognition

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An Intelligent Approach for Robust Detection and Recognition of Multiple Color and Font Styles Automobiles License Plates: A Feature-Based algorithm 4

An Intelligent Approach for Robust Detection and Recognition...

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International Conference on Audio, Language and Image Processing

作者： Bhutta, M. Usman Maqbool Mahmood, Hasan Malik, Hafiz Quaid I Azam Univ Dept Elect Islamabad Pakistan Univ Michigan Dept Elect & Comp Engn Dearborn MI 48128 USA

ISBN: (纸本)9781479939039

This paper presents a robust real time feature based algorithm for localization and recognition of multiple color and font style license plates. The algorithm uses digitized license plate images for robust detection and recognition. The resolution of the captured image is adjusted and the brightness and contrast are set to appropriate levels. An optimal threshold is applied to detect white regions of the enhanced image. The algorithm uses segmentation and component labeling to create candidate regions intelligently. For localization of the license plate, features of each region are extracted and analyzed by rectangularity percentage of the automobile's license plate. The use of color filter renders the algorithm more robust on license plate localization. Moreover, we use HSV color space to find the specific color regions. After localization of license plate in small sized image, the proposed algorithm uses rapid intelligent method for localization of license plate form the original image. The localized license plate image is cropped and processed by the recognition algorithm. Each character's region is identified by using segmentation algorithm based on the profile which includes character dilation and resizing for subsequent operations. In this paper, correlation optical character recognition and multi-layer perception neural networks techniques are used for recognizing the characters. The performance of the proposed algorithm is acceptable even in low-quality or bad light images.

关键词： correlation methods image colour analysis image enhancement image resolution image segmentation multilayer perceptrons optical character recognition traffic engineering computing HSV color space character dilation color detection color filter color localization color recognition component labeling correlation optical character recognition digitized license plate images feature-based algorithm font style license plate localization font styles automobile license plate recognition intelligent approach multilayer perception neural networks optimal threshold region extraction segmentation algorithm white region detection Correlation Feature extraction Image color analysis Image segmentation Licenses Neural networks Vehicles License plates image colour analysis image resolution image enhancement image segmentation COLOR FILTER optical character recognition Licence licensing Multilayer perceptrons correlation methods color spaces Neural network Feature extraction vehicle

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A new approach to diagnosis of pulmonary embolism using multi-slice CT

A new approach to diagnosis of pulmonary embolism using mult...

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Medical Imaging 2001 Conference

作者： Niethammer, MU Schoepf, UJ Wildberger, JE Klotz, E Fichte, H Schaller, S Siemens Med Solut Comp Tomog D-91301 Forchheim Germany

ISBN: (纸本)0819440078

Suspected pulmonary embolism (PE) is a common indication for CT scanning of the thorax. Usually, intravenous contrast agent is administered utilizing a power-injector and the vascular structures are examined for the presence of pulmonary emboli. Current Multi-Slice CT-technology allows extending this morphological analysis by adding a more functional visualization of the actual parenchymal perfusion disturbance. We have developed a new image processing technique which allows selective color encoded display of parenchymal enhancement of the lung, which will be reduced in the presence of PE. Based on thin slice reconstructions an automatic 3D segmentation of the lung is performed followed by threshold based extraction of the major airways and vascular structures. This allows applying an adaptive 3D low-pass filter to the parenchymal volume only. The filtered volume data are then color encoded and overlaid onto the original CT-images. This combination of low-resolution perfusion-weighted color maps and high-resolution gray scale structural data from the same data set greatly enhances visualization of spatial relationships. The resulting images can be displayed in axial, sagittal and coronal orientation. Initial experience indicates that this new technique provides relevant additional information for the clinical management of patients with proven PE. A larger controlled patient study is under way.

关键词： lung perfusion parenchymography segmentation algorithm pulmonary embolism computed tomography (CT)

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Within-field zoning using a region growing algorithm guided by geostatistical analysis

Within-field zoning using a region growing algorithm guided ...

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9th European Conference on Precision Agriculture

作者： Zane, L. Tisseyre, B. Guillaume, S. Charnomordic, B. INRA UMR MISTEA F-34060 Montpellier France UMR ITAP Montpellier SupAgro Cemagref F-34060 Montpellier France

ISBN: (纸本)9789086862245

Region growing methods are of potential interest to define within-field zones and resulting site-specific management. These methods are unsupervised and based on regions which grow from the initial seeds according to homogeneity criteria. However, the determination of seed number and seed locations has strong repercussions on the zoning output. This paper proposes an approach to allow knowledge inherited from geostatistical analysis to guide the seed initialization (seed number and location) of a region growing-based segmentation method. In this study, the segmentation method is a general division/merging procedure which, in this study, is used for merging and region growing. An original point is the possibility to use it either for irregularly located data or data arranged on a regular grid. The initialization of the segmentation method is guided by a prior analysis where a few parameters of the semi-variogram model are used to set: (1) the number of seeds required to initialize the region growing procedure;(2) to decide their relative locations (i e minimal distance between seeds);and (3) to identify potential outliers as seeds that may flaw the growing procedure. Both methods were tested on two data sets: (1) three hypothetical fields of known distribution and known spatial organization;(2) a real field where yield monitor data were obtained. A qualitative analysis of the results is presented, as well as the evolution of the variance explained by the model.

关键词： zoning segmentation algorithm growing region geostatistics

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Investigating the Correlation between Swallow Accelerometry Signal Parameters and Anthropometric and Demographic Characteristics of Healthy Adults

Investigating the Correlation between Swallow Accelerometry ...

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作者： Hanna, Fady University of Toronto

学位级别：master

Thesis studied correlations between swallowing accelerometry parameters and anthropometrics in 50 healthy participants. Anthropometrics include: age, gender, weight, height, body fat percent, neck circumference and mandibular length. Dual-axis swallowing signals, from a biaxial accelerometer were obtained for 5-saliva and 10-water (5-wet and 5-wet chin-tuck) swallows per participant. Two patient-independent automatic segmentation algorithms using discrete wavelet transforms of swallowing sequences segmented: 1) saliva/wet swallows and 2) wet chin-tuck swallows. Extraction of swallows hinged on dynamic thresholding based on signal *** correlation analysis was performed on sets of anthropometric and swallowing signal variables including: variance, skewness, kurtosis, autocorrelation decay time, energy, scale and peak-amplitude. For wet swallows, significant linear relationships were found between signal and anthropometric variables. In superior-inferior directions, correlations linked weight, age and gender to skewness and signal-memory. In anterior-posterior directions, age was correlated with kurtosis and signal-memory. No significant relationship was observed for dry and wet chin-tuck swallowing

关键词： aspiration Accelerometry Anthropometric Canonical Correlation segmentation algorithm

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White Spot Syndrome Detection in Shrimp using Neural Network Model 18

White Spot Syndrome Detection in Shrimp using Neural Network...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Vembarasi, K. Thotakura, Vishnu Priya Senthilkumar, S. Ramachandran, L. Lakshmi Praba, V. Vetriselvi, S. Chinnadurai, M. E.G.S. Pillay Engineering College Department of Electronics and Communication Engineering Nagapattinam India Srk Institute of Technology Department of Electronics and Communication Engineering Vijayawada India E.G.S. Pillay Engineering College Department of Computer Science and Engineering Nagapattinam India

ISBN: (纸本)9789380544519

White Spot Syndrome Virus (WSSV) epidemics have seriously harmed penaeid shrimp aquaculture all over the world. There remains an absence of information concerning these complicated viral-host interactions, despite significant attempts to describe the virus, the circumstances that cause infection, and the processes of infection. This understanding is required to develop reliable and efficient treatment strategies for WSSV. Mechanisms for segmenting and categorizing images offer a method for extracting features from images based on their objects. Those certain objects are produced using an image segmentation technique in which segments are formed by grouping together pixels with similar spectral properties that are close to one another. The area of interest on any underlying image is protected by image segmentation, a crucial step before actual analysis is recommended in any image processing methodology. In fact, the effectiveness of the segmentation algorithm used will have a big impact on how accurate any image processing performs. This study proposes a typical segmentation technique for segmenting shrimp variability by using essential Canny-GLCM (Gray Level Co-occurrence Matrix) features with a simple Artificial Neural Network (ANN) model. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Artificial Neural Network segmentation algorithm shrimp White spot syndrome virus

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A BST-based Approach to Dictionary Structure for Chinese Word segmentation

A BST-based Approach to Dictionary Structure for Chinese Wor...

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2011 IEEE International Conference on Computer Science and Automation Engineering(CSAE 2011)

作者： Chang Ge,Ningjing Ma and Xudong Chen National Pilot School of Software Engineering Beijing Jiaotong University Beijing,P.R.China

This paper firstly analyzes current Chinese word segmentation methods,and then bases on word dictionary segmentation and binary search tree(BST) proposing a way to organize the dictionary which focuses on reducing comparison times in order to increase the segmentation *** that,a practical demo is used to illustrate the feasibility and effectiveness of the proposed algorithm.

关键词： word segmentation dictionary structure binary serach tree segmentation algorithm

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Gotta Trace 'em All: A Mini-Review on Tools and Procedures for Segmenting Single Neurons Toward Deciphering the Structural Connectome

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FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY 2019年第AUG期7卷 202-202页

作者： Magliaro, Chiara Callara, Alejandro L. Vanello, Nicola Ahluwalia, Arti Univ Pisa Res Ctr E Piaggio Pisa Italy Univ Pisa Dipartimento Ingn Informaz Pisa Italy

Decoding the morphology and physical connections of all the neurons populating a brain is necessary for predicting and studying the relationships between its form and function, as well as for documenting structural abnormalities in neuropathies. Digitizing a complete and high-fidelity map of the mammalian brain at the micro-scale will allow neuroscientists to understand disease, consciousness, and ultimately what it is that makes us humans. The critical obstacle for reaching this goal is the lack of robust and accurate tools able to deal with 3D datasets representing dense-packed cells in their native arrangement within the brain. This obliges neuroscientist to manually identify the neurons populating an acquired digital image stack, a notably time-consuming procedure prone to human bias. Here we review the automatic and semi-automatic algorithms and software for neuron segmentation available in the literature, as well as the metrics purposely designed for their validation, highlighting their strengths and limitations. In this direction, we also briefly introduce the recent advances in tissue clarification that enable significant improvements in both optical access of neural tissue and image stack quality, and which could enable more efficient segmentation approaches. Finally, we discuss new methods and tools for processing tissues and acquiring images at sub-cellular scales, which will require new robust algorithms for identifying neurons and their sub-structures (e.g., spines, thin neurites). This will lead to a more detailed structural map of the brain, taking twenty-first century cellular neuroscience to the next level, i.e., the Structural Connectome.

关键词： structural connectome segmentation algorithm 3D neuron segmentation single-cell segmentation CLARITY

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