Robust sequential surface based object segmentation in noisy range data

1995 ◽  
Author(s):  
M.J. Mirza
Keyword(s):  
Object Segmentation ◽  
Range Data

INTEGRATION OF 2D IMAGES AND RANGE DATA FOR OBJECT SEGMENTATION AND RECOGNITION

2009 ◽  
Author(s):  
Neslihan Bayramoğlu ◽  
Oytun Akman ◽  
A. Aydm Alatan ◽  
Pieter Jonker
Keyword(s):  
Object Segmentation ◽  
Range Data ◽  
2D Images

IMPROVED OBJECT SEGMENTATION USING MULTI SCALE SALIENCY APPROACH

2018 ◽  
Vol 6 (4) ◽  
pp. 161-167
Author(s):  
S. Thilagamani ◽  
◽  
◽  
V. Manochitra
Keyword(s):  
Object Segmentation ◽  
Multi Scale

Segmentasi Citra Mri Menggunakan Deteksi Tepi Untuk Identifikasi Kanker Payudara

2017 ◽  
Vol 15 (2) ◽  
pp. 17 ◽  
Author(s):  
Ervina Varijki ◽  
Bambang Krismono Triwijoyo
Keyword(s):  
Breast Cancer ◽  
Edge Detection ◽  
Object Segmentation ◽  
Computation Time ◽  
Input Image ◽  
Boundary Line ◽  
Cancer Breast ◽  
Average Computation Time ◽  
Breast Cancer Mri ◽  
Image Format

One type of cancer that is capable identified using MRI technology is breast cancer. Breast cancer is still the leading cause of death world. therefore early detection of this disease is needed. In identifying breast cancer, a doctor or radiologist analyzing the results of magnetic resonance image that is stored in the format of the Digital Imaging Communication In Medicine (DICOM). It takes skill and experience sufficient for diagnosis is appropriate, andaccurate, so it is necessary to create a digital image processing applications by utilizing the process of object segmentation and edge detection to assist the physician or radiologist in identifying breast cancer. MRI image segmentation using edge detection to identification of breast cancer using a method stages gryascale change the image format, then the binary image thresholding and edge detection process using the latest Robert operator. Of the20 tested the input image to produce images with the appearance of the boundary line of each region or object that is visible and there are no edges are cut off, with the average computation time less than one minute.

Video Object Segmentation Research Based on Features Joint Modeling

2014 ◽  
Vol 36 (11) ◽  
pp. 2356-2363
Author(s):  
Zong-Min LI ◽  
Xu-Chao GONG ◽  
Yu-Jie LIU
Keyword(s):  
Object Segmentation ◽  
Joint Modeling ◽  
Video Object Segmentation ◽  
Video Object

MOMENTUM OSCILLATORS - A TOOL TO PREDICT STOCK PRICE BEHAVIOUR

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Shishir Kumar Gujrati
Keyword(s):  
Stock Price ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Future Price ◽  
Range Data ◽  
Strength Index ◽  
Price Trends ◽  
Past Data ◽  
Price Movements

Stock markets are always taken as the barometer of the economy. The price movement of their indices reflects every ups and downs of the economy. Although seem to be random, these price movements do follow a certain track which can be identified using appropriate tool over long range data. One such method is of Technical Analysis wherein future price trends are forecasted using past data. Momentum Oscillators are the important tools of technical analysis. The current paper aims to identify the previous price movements of sensex by using Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) tools and also aims to check whether these tools are appropriate in forecasting the price trends or not.

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