Search

  • Select Article Type
  • Abstract Supplements
  • Blood Group Review
  • Call to Arms
  • Hypothesis
  • In Memoriam
  • Interview
  • Introduction
  • Short Report
  • abstract
  • Abstracts
  • Article
  • book-review
  • case-report
  • case-study
  • Clinical Practice
  • Commentary
  • Conference Presentation
  • conference-report
  • congress-report
  • Correction
  • Editorial
  • Editorial Comment
  • Erratum
  • Events
  • Letter
  • Letter to Editor
  • mini-review
  • minireview
  • News
  • non-scientific
  • Obituary
  • original-paper
  • Original Research
  • Pictorial Review
  • Position Paper
  • Practice Report
  • Preface
  • Preliminary report
  • Product Review
  • rapid-communication
  • Report
  • research-article
  • Research Communicate
  • research-paper
  • Research Report
  • Review
  • review -article
  • review-article
  • Review Paper
  • Sampling Methods
  • Scientific Commentary
  • short-communication
  • short-report
  • Student Essay
  • Varia
  • Welome
  • Select Journal
  • In Jour Smart Sensing And Intelligent Systems
  • International Journal Advanced Network Monitoring Controls
  • Architecture Civil Engineering Environment
  • Statistics In Transition

 

Article

Review of 3D Point Cloud Data Segmentation Methods

I. INTRODUCTION Image segmentation is one of the basic research directions of computer vision, and its purpose is to subdivide a digital image into multiple regions with similar properties[1]. Segmentation of 2D images has more than 50 years of research history, but 3D point cloud data is a highly redundant and irregularly ordered structure, point cloud segmentation also faces many challenges. The segmentation of point clouds into foreground and background is a fundamental step in processing 3D

Xiaoyi Ruan, Baolong Liu

International Journal of Advanced Network, Monitoring and Controls , ISSUE 1, 66–71

Article

IMAGE SEGMENTATION ALGORITHM BASED ON COLOR FEATURES: CASE STUDY WITH GIANT PANDA

Color which is one of the basic features of the image is widely used in image processing. The choice of color space is a primary issue for the color image segmentation based on color features. In this paper, giant pandas are chosen as the research objects. In order to achieve good segmentation results, different color spaces and the corresponding algorithms are chosen for image segmentation according to the color characteristics of different background of panda images. There are three kinds of

Hua Wang, Jiang Xiao, Junguo Zhang

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 799–817

Article

AUTOMATIC HUMAN DAILY ACTIVITY SEGMENTATION APPLYING SMART SENSING TECHNOLOGY

Human daily activity segmentation utilizing smartphone sensing technology is quite new challenge. In this paper, the segmentation method combining statistical model and time series analysis is designed and implemented. According to designed partition procedure, real measured accelerometer datasets of human daily activities are tested. The segmentation performance of sliding window autocorrelation and minimized contrast algorithms is analysed and compared. Experiments demonstrate the

Yin Ling

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1624–1640

Research paper

A Lexicon-Corpus-based Unsupervised Chinese Word Segmentation Approach

This paper presents a Lexicon-Corpus-based Unsupervised (LCU) Chinese word segmentation approach to improve the Chinese word segmentation result. Specifically, it combines advantages of lexicon-based approach and Corpus-based approach to identify out-of-vocabulary (OOV) words and guarantee segmentation consistency of the actual words in texts as well. In addition, a Forward Maximum Fixed-count Segmentation (FMFS) algorithm is developed to identify phrases in texts at first. Detailed rules

Lu Pengyu, Pu Jingchuan,, Du Mingming, Lou Xiaojuan, Jin Lijun

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 263–282

Article

AUTOMATIC SEGMENTATION OF BRAIN TUMOR MAGNETIC RESONANCE IMAGING BASED ON MULTI-CONSTRAINS AND DYNAMIC PRIOR

The most difficult and challenging problem in medical image analysis is image segmentation. Due to the limited imaging capability of magnetic resonance (MR), the sampled magnetic resonance images from clinic always suffer from noise, bias filed (also known as intensity non-uniformity), partial volume effects and motive artifacts. In additional, for the complex shape boundary and topology of brain tissues and structures, segmenting magnetic resonance image of brain tumor fast, accurately and

Liu Erlin, Wang Meng, Teng Jianfeng, Li Jianjian

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 1031–1049

Article

Analysis and Design of Image Segmentation Algorithm Based on Super-pixel and Graph Cut

I. INTRODUCTION Image segmentation is the division process of independent regions in an image with particular meaning which makes the same region represent the same features. The purpose is extracting the interesting parts called “the foreground”, and the rest parts are called “the background”. However, the characteristic differences between the foreground and the background may be reflected in various aspects such as grayscale, contour, texture, etc., so there is currently no general algorithm

Feng Xiao, Hao Sun

International Journal of Advanced Network, Monitoring and Controls , ISSUE 4, 25–30

Article

Fast Aerial UAV Detection Based on Image Segmentation and HOG-FLD Feature Fusion

In order to detect non-cooperative target UAV quickly and accurately, a novel method of UAV detection method based on graph theory and HOG-FLD feature fusion is presented in this paper. In order to avoid the time-consuming full search, the candidate areas of the UAV are obtained through the selective search of the image segmentation and the similarity, and the features are extracted through the method of gradient orientation histogram fusion FLD linear to train the SVM classifier with

Li Xiaoping, Lei Songze, Wang Yanhong, Xiao Feng, Penghui Tian

International Journal of Advanced Network, Monitoring and Controls , ISSUE 1, 106–114

Article

COMPUTER VISION-BASED COLOR IMAGE SEGMENTATION WITH IMPROVED KERNEL CLUSTERING

Color image segmentation has been widely applied to diverse fields in the past decades for containing more information than gray ones, whose essence is a process of clustering according to the color of pixels. However, traditional clustering methods do not scale well with the number of data, which limits the ability of handling massive data effectively. We developed an improved kernel clustering algorithm for computing the different clusters of given color images in kernel-induced space for

Yongqing Wang, Chunxiang Wang

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1706–1729

Article

OVERLAPPING WHITE BLOOD CELL SEGMENTATION AND COUNTING ON MICROSCOPIC BLOOD CELL IMAGES

Overlapping white blood cell identification on microscopic blood cell images is proposed for increasing the accuracy of white blood cell segmentation and counting. The accurate identification of overlapping cells can increase the accuracy of cell counting system for diagnosing diseases. The overlapping cells have different characteristic such as area and shape with a single cell of microscopic cell images therefore the overlapping cell identification based on geometric feature is preferred. As

Chastine Fatichah, Diana Purwitasari, Victor Hariadi, Faried Effendy

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1271–1286

Article

APTIVE IMAGE SEGMENTATION BASED ON SALIENCY DETECTION

in this article, we propose an adaptive image segmentation method based on saliency. First of all, we obtain the saliency map of an image via four bottom-layer feature tunnels, i.e. color, intensity, direction and energy. The energy tunnel helps to describe the outline of objects better in the saliency map. Then, we construct the target detection masks according to the greyness of pixels in the saliency map. Each mask is applied to the original image as the result of pre-segmentation, then

Shui Linlin

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 408–428

Article

A HYBRID FUZZY MORPHOLOGY AND CONNECTED COMPONENTS LABELING METHODS FOR VEHICLE DETECTION AND COUNTING SYSTEM

A hybrid fuzzy morphology and connected components labeling method is proposed for detecting and counting the number of vehicles in an image taken from a traffic monitoring camera. A fuzzy morphology approach in image segmentation method is used in the system to achieve faster computation time compared to the supervised learning. The connected components labeling method is combined with a fuzzy morphology method to determine the region and number of objects in an image. The processing phases in

Chastine Fatichah, Joko Lianto Buliali, Ahmad Saikhu, Silvester Tena

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 765–779

Article

A NOVEL KNOWLEDGE-COMPATIBILITY BENCHMARKER FOR SEMANTIC SEGMENTATION

Vektor Dewanto, Aprinaldi, Zulfikar Ian, Wisnu Jatmiko

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 1284–1312

Research Article

STUDY OF VISION BASED HAND GESTURE RECOGNITION USING INDIAN SIGN LANGUAGE

as hand plays vital communication mode. Considering earlier reported work, various techniques available for hand tracking, segmentation, feature extraction and classification are listed. Vision based system have challenges over traditional hardware based approach; by efficient use of computer vision and pattern recognition, it is possible to work on such system which will be natural and accepted, in general.

Archana S. Ghotkar, Dr. Gajanan K. Kharate

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 96–115

Article

SPECTRAL CLUSTERING WITH SPATIAL COHERENCE PROPERTY JOINTING TO ACTIVE CONTOUR MODEL FOR IMAGE LOCAL SE GMENTATION

Local Segmentation is the fundamental task for image processing. Consider to the problem of low segmentation precision and contour control instability for image local segmentation, a local segmentation theory is researched that based on SSCACM (spectral clustering with spatial coherence property jointing active contour model). First, by applying spatial coherence property constraint of image pixels to spectral clustering, an adaptive similarity function is constructed and the corresponding

Guang Hu, Shengzhi Yuan

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 1731–1749

Article

A NOVEL GRID INTERSECTION POINT DETECTION AND MATCHING METHOD IN THE BINOCULAR PULSE MEASUREMENT SYSTEM

To improve the accuracy of binocular 3D image reconstruction, the grid-pattern structure lines are printed on the detected objects and the grid lines intersection points are adopted as feature points and primitives in matching process. In this paper, a novel method for detecting the intersection points of the grid lines based on image segmentation and ridge line fitting is proposed. Firstly, the set of line segments on the border of the grid lines are extracted using the Canny edge detector and

L. M. Yang, A. H. Zhang, D. M. Lin, L. Zhu

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 256–273

Research Article

FEATURES OF SLEEP APNEA RECOGNITION AND ANALYSIS

greatly improves when the number of samples was greatly decreased and very high peaks and more complex parts of the signal were excluded in the analysis. Segmentation was also conducted and the segmentation error revealed when an Event Related Potential (ERP) has happened which is when apnea occurred.

LEONG WAI YIE, JOEL THAN CHIA MING

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 481–497

Article

FACE DETECTION IN PROFILE VIEWS USING FAST DISCRETE CURVELET TRANSFORM (FDCT) AND SUPPORT VECTOR MACHINE (SVM)

Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial expression recognition, and the like. This paper presents a profile face detection algorithm based on curvelet features, as curvelet transform offers good directional representation and can capture edge information in human face from different angles. First, a simple skin color segmentation scheme based on HSV (Hue – Saturation - Value) and

Bashir Muhammad, Syed Abd Rahman Abu-Bakar

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 108–123

Article

Research on Harris Corner Detection Method in Palmprint Recognition System

Hejing Wu

International Journal of Advanced Network, Monitoring and Controls , ISSUE 1, 72–76

research-article

Indonesian traffic sign detection based on Haar-PHOG features and SVM classification

objects. Moreover, traffic signs might be physically faded and damaged due to vandalism, making it harder to detect their color and shape. Segmentation is used to separate the color of traffic signs from the background, which is then continued with shape search to find candidates based on feature extraction. Researches on shape features mostly use Histogram of Oriented Gradient (HOG) and Pyramid Histogram of Oriented Gradient (PHOG). HOG uses blocks and cells to determine shape features. In order to

Aris Sugiharto, Agus Harjoko, Suharto Suharto

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 1–15

Article

ROAD DAMAGE IDENTIFICATION AND DEGREE ASSESSMENT BASED ON UGV

Aiming at the problem of automatic identification and evaluation of road damage degree, the road damage identification and degree assessment algorithms based on unmanned vehicles experimental platform are studied. The road crack segmentation extraction method based on adaptive sliding window is studied. On this basis, the road damage crack classifies and identifies according to the crack geometry information and the principle of template matching. The road damage degree assessment algorithm

J. H. Song, H. W. Gao, Y. J. Liu, Y. Yu

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 2069–2087

Article

IMAGE PROCESSING AND RECOGNITION ALGORITHM FOR TARGET TRACKING

to improve target tracking performance in dynamic target track system, this paper propose the processing method of positive and negative difference image to extract target information; research target image preprocessing algorithm, the separation and segmentation processing algorithm of target and background, target edge detection and extraction based on the collected images; use Laplace operator, Canny operator. Gauss-Laplace operator to gain target information and improved recognition target

Liping Lu, Jinfang Wang

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 353–376

Article

RECOGNITION OF THE STACKED OBJECTS FOR BIN PICKING

local minimum problem exists in recognition of the objects. We propose the method to recognize the stacked objects statistically using multiple recognition result. Avoidance of the local minimum problem and the segmentation of each objects are performed by recognizing statistically.

M. Hikizu, S. Mikami, H. Seki

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1177–1188

Article

FOREGROUND DETECTION IN SURVEILLANCE VIDEOS VIA A HYBRID LOCAL TEXTURE BASED METHOD

Foreground detection is a basic but challenging task in computer vision. In this paper, a novel hybrid local texture based method is presented to model the background for complex scenarios and an image segmentation based denoising processing is applied to reduce noise. We combine the uniform pattern of eXtended Center-Symmetric Local Binary Pattern (XCS-LBP) and Center- Symmetric Local Derivative Pattern (CS-LDP) to generate a discriminative feature with shorter histogram. Retaining the

Xiaojing Du, Guofeng Qin

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 1668–1686

Research Article

PERFORMANCE AND ANALYSIS OF AUTOMATIC LICENSE PLATE LOCALIZATION AND RECOGNITION FROM VIDEO SEQUENCES

database number plates for authentication. The proposed model has low complexity and less time consuming interms of number plate segmentation and character recognition. This can improve the system performance and make the system more efficient by taking relevant sample.

M.Anto Bennet, B. Thamilvalluvan, Priyanka Paree Alphonse, D.R. Thendralarasi, K. Sujithra

International Journal on Smart Sensing and Intelligent Systems , ISSUE 5, 330–343

Article

NEW METHOD OF VARIABLE SELECTION FOR BINARY DATA CLUSTER ANALYSIS

Jerzy Korzeniewski

Statistics in Transition New Series , ISSUE 2, 295–304

research-article

GEOSPATIAL DATA PROCESSING CHARACTERISTICS FOR ENVIRONMENTAL MONITORING TASKS

homogeneity in each of its fragments, the most appropriate is the use of the “nearest neighbor” method [13, 15, 21]. To achieve the level of homogeneity in automatic segmentation, the use of the brightness segmentation method is proposed. At the same time, other methods for clustering data were considered, determining the differences in the values of segmentation parameters (in accordance with the established criteria when constructing the “criterion trees”), the corresponding boundaries between the

Olga BUTENKO, Stanislav HORELIK, Oleh ZYNYUK

Architecture, Civil Engineering, Environment , ISSUE 1, 103–114

Research Article

AUDIOVISUAL SENSING OF HUMAN MOVEMENTS FOR HOME-CARE AND SECURITY IN A SMART ENVIRONMENT

Liyanage C De Silva

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 220–245

No Record Found..
Page Actions