Connected-component labeling ≈ Connected-component labeling
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The connected-component labeling problem: A review of state-of-the-art algorithms Open
This article addresses the connected-component labeling problem which consists in assigning a unique label to all pixels of each connected component (i.e., each object) in a binary image. Connected-component labeling is indispensable for d…
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Automatic Vehicle License Plate Recognition Using Optimal K-Means With Convolutional Neural Network for Intelligent Transportation Systems Open
Due to recent developments in highway research and increased utilization of vehicles, there has been significant interest paid on latest, effective, and precise Intelligent Transportation System (ITS). The process of identifying particular…
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License Plate Detection Using Harris Corner and Character Segmentation by Integrated Approach from an Image Open
This paper addresses License Plate localization with the integrated segmentation approach. As the significance of open travel framework builds an Automatic License Plate Recognition has ended up being a critical exploration subject. ALPR f…
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Toward an Optimized Neutrosophic k-Means With Genetic Algorithm for Automatic Vehicle License Plate Recognition (ONKM-AVLPR) Open
The present paper proposes a new methodology for license plate (LP) recognition in the state of the art of image processing algorithms and an optimized neutrosophic set (NS) based on genetic algorithm (GA). First of all, we have performed …
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YACCLAB - Yet Another Connected Components Labeling Benchmark Open
The problem of labeling the connected components (CCL) of a binary image is well-defined and several proposals have been presented in the past. Since an exact solution to the problem exists and should be mandatory provided as output, algor…
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Towards Automatic License Plate Detection Open
Automatic License Plate Detection (ALPD) is an integral component of using computer vision approaches in Intelligent Transportation Systems (ITS). An accurate detection of vehicles’ license plates in images is a critical step that has a su…
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Dental Images’ Segmentation Using Threshold Connected Component Analysis Open
Recent advances in medical imaging analysis, especially the use of deep learning, are helping to identify, detect, classify, and quantify patterns in radiographs. At the center of these advances is the ability to explore hierarchical featu…
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Spinal Cord Based Kidney Segmentation Using Connected Component Labeling and K-Means Clustering Algorithm Open
Abdominal computed tomography (CT) data are often used in the diagnosis and treatment of patients.Segmentation of viscera on abdominal imaging facilitates diagnosis and focus upon the areas of interest.Kidney segmentation by abdominal imag…
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Touching text line segmentation combined local baseline and connected component for Uchen Tibetan historical documents Open
The text lines of ancient Tibetan books are skewed and distorted, strokes are broken, and complex adjacent text lines touch each other, which makes text line segmentation extremely challenging. In this paper, a text line segmentation metho…
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Zig-Zag Based Single-Pass Connected Components Analysis Open
Single-pass connected components analysis (CCA) algorithms suffer from a time overhead to resolve labels at the end of each image row. This work demonstrates how this overhead can be eliminated by replacing the conventional raster scan by …
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Traffic Light Recognition Based on Binary Semantic Segmentation Network Open
A traffic light recognition system is a very important building block in an advanced driving assistance system and an autonomous vehicle system. In this paper, we propose a two-staged deep-learning-based traffic light recognition method th…
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Distributed Connected Component Filtering and Analysis in 2D and 3D Tera-Scale Data Sets Open
Connected filters and multi-scale tools are region-based operators acting on the connected components of an image. Component trees are image representations to efficiently perform these operations as they represent the inclusion relationsh…
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Grasping Point Detection of Randomly Placed Fruit Cluster Using Adaptive Morphology Segmentation and Principal Component Classification of Multiple Features Open
Precise and rapid grasping point detection based on machine vision is one of the challenging problems in automatic sorting of randomly placed fruit clusters by robot. Grasping stalk of fruit cluster can improve grasping success probability…
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Co-Segmentation and Superpixel-Based Graph Cuts for Building Change Detection from Bi-Temporal Digital Surface Models and Aerial Images Open
Thanks to the recent development of laser scanner hardware and the technology of dense image matching (DIM), the acquisition of three-dimensional (3D) point cloud data has become increasingly convenient. However, how to effectively combine…
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Human Skin Region Segmentation Based on Chrominance Component Using Modified Watershed Algorithm Open
A novel watershed segmentation algorithm has been proposed to segment the human skin region of RGB color images based on Cb component of YCbCr color space in this paper. The conventional watershed segmentation algorithm is not suitable for…
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Real-Time FPGA Implementation of Parallel Connected Component Labelling for a 4K Video Stream Open
In this paper, a hardware implementation in reconfigurable logic of a single-pass connected component labelling (CCL) and connected component analysis (CCA) module is presented. The main novelty of the design is the support of a video stre…
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Efficient Parallel Connected Component Labeling With a Coarse-to-Fine Strategy Open
This paper proposes a new parallel approach to solve connected components on a 2-D binary image. The following strategies are employed to accelerate neighborhood exploration after dividing an input image into independent blocks: 1) in the …
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An Automatic Cognitive Graph-Based Segmentation for Detection of Blood Vessels in Retinal Images Open
This paper presents a hierarchical graph-based segmentation for blood vessel detection in digital retinal images. This segmentation employs some of perceptual Gestalt principles: similarity, closure, continuity, and proximity to merge segm…
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GPU-Accelerated Foreground Segmentation and Labeling for Real-Time Video Surveillance Open
Real-time and accurate background modeling is an important researching topic in the fields of remote monitoring and video surveillance. Meanwhile, effective foreground detection is a preliminary requirement and decision-making basis for su…
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K-mean clustering and local binary pattern techniques for automatic brain tumor detection Open
Tumors in brains are caused by the unregulated emergence of tissue cells inside the brain. The early diagnosis and determining the precise location of the tumor in magnetic resonance imaging (MRI) and its size are essential for the teams o…
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ID card number detection algorithm based on convolutional neural network Open
In this paper, a new detection algorithm based on Convolutional Neural Network is presented in order to realize the fast and convenient ID information extraction in multiple scenarios. The algorithm uses the mobile device equipped with And…
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An Improved Otsu’s Thresholding Algorithm on Gesture Segmentation Open
In gesture recognition systems, segmenting gestures from complex background is the hardest and the most critical part. Gesture segmentation is the prerequisite of following image processing, and the result of segmentation has a direct infl…
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Graph Convolutional Networks for Semi-Supervised Image Segmentation Open
The problem of image segmentation is one of the most significant ones in computer vision. Recently, deep-learning methods have dominated state-of-the-art solutions that automatically or interactively divide an image into subregions. Howeve…
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Semantic Segmentation under a Complex Background for Machine Vision Detection Based on Modified UPerNet with Component Analysis Modules Open
Semantic segmentation with convolutional neural networks under a complex background using the encoder-decoder network increases the overall performance of online machine vision detection and identification. To maximize the accuracy of sema…
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Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method Open
In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area o…
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A Zone Classification Approach for Arabic Documents using Hybrid Features Open
Zone segmentation and classification is an important step in document layout analysis. It decomposes a given scanned document into zones. Zones need to be classified into text and non-text, so that only text zones are provided to a recogni…
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A fast and memory-efficient two-pass connected-component labeling algorithm for binary images Open
Connected-component labeling is an important process in image analysis and pattern recognition. It aims to deduct the connected components by giving a unique label value for each individual component. Many algorithms have been proposed, bu…
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Distributed Component Forests in 2-D: Hierarchical Image Representations Suitable for Tera-Scale Images Open
The standard representations known as component trees, used in morphological connected attribute filtering and multi-scale analysis, are unsuitable for cases in which either the image itself or the tree do not fit in the memory of a single…
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An ISAR Image Component Recognition Method Based on Semantic Segmentation and Mask Matching Open
The inverse synthetic aperture radar (ISAR) image is a kind of target feature data acquired by radar for moving targets, which can reflect the shape, structure, and motion information of the target, and has attracted a great deal of attent…
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Ancient Chinese Character Image Segmentation Based on Interval-Valued Hesitant Fuzzy Set Open
To address the low segmentation accuracy caused by the rich glyph styles of ancient Chinese characters and the complex layout of ancient Chinese books, which affects the retrieval and recognition results, an algorithm for the layout image …