A Motion Edge Extraction Method under the Condition of Camera Swing

2014 ◽  
Vol 513-517 ◽  
pp. 3878-3881
Author(s):  
Xiao Qing Wu ◽  
Xiang Long ◽  
Xiong Yang
Keyword(s):  
Extraction Method ◽  
Motion Segmentation ◽  
Test Sequence ◽  
Edge Extraction ◽  
Motion Model ◽  
Segmentation Methods ◽  
Background Pixel

Motion edge extraction is the object of most motion segmentation methods. We have proposed a motion edge extraction method in our previous work. However, if the camera swings, a number of background edges are classified into foreground edges. In order to solve this problem, we propose a background pixel relating method to modify the motion model and to remove those misclassified edges. At the end of this paper, we use the CAVIAR project test sequence to test our method. The result is satisfactory.

Histogram of Marked Background (HMB) Feature Extraction Method for Arabic Handwriting Recognition

2021 ◽  
pp. 2250015
Author(s):  
Meriem Gagaoua ◽  
Hamza Ghilas ◽  
Abdelkamel Tari ◽  
Mohamed Cheriet
Keyword(s):  
Extraction Method ◽  
Markov Models ◽  
Hidden Markov ◽  
Handwriting Recognition ◽  
Features Extraction ◽  
Complex Nature ◽  
Ibn Sina ◽  
Feature Extraction Method ◽  
Recognition Systems ◽  
Background Pixel

Features extraction is one of the most important steps in handwriting recognition systems. In this paper, we propose a novel features extraction method, which is adapted to the complex nature of Arabic handwriting. The proposed feature called histogram of marked background (HMB) is not considering only ink pixels in a text image, but also uses the background of the image. Each background pixel in the text image was marked according to the repartition of ink pixels in its neighborhood. Feature vectors are extracted by computing histograms from the marked images. Hidden Markov models (HMMs) with Hidden Markov model toolkit (HTK) were used in the recognition process. The experiments were performed on two datasets: IBN SINA database of historical Arabic documents and Isolated Farsi Handwritten Character Database (IFHCDB). The proposed feature in this study produced efficient and promising results for Arabic handwriting recognition, for both isolated characters and for historical documents.

An Edge Extraction Method Based on Gradient with ACS

2010 ◽  
Vol 39 (4) ◽  
pp. 759-763
Author(s):  
陈亮 CHEN Liang ◽  
郭雷 GUO Lei
Keyword(s):  
Extraction Method ◽  
Edge Extraction

Image Edge Extraction Based on SUSAN Operator

2014 ◽  
Vol 687-691 ◽  
pp. 3765-3768
Author(s):  
Nan Wang
Keyword(s):  
Edge Detection ◽  
High Precision ◽  
Extraction Method ◽  
The Other ◽  
Differential Detection ◽  
Edge Extraction ◽  
Image Edge ◽  
Circular Template

A new edge extraction method was put forward based on the SUSAN operator, according to the problems of poor anti-noise ability and edge detection incomplete of the conventional differential detection operator. The circular template and the center of the circle (template nuclear) were used in this method, the numbers of pixels was calculated through the comparison pixels value of template with the other points of pixels in the template circle, and then compared with the threshold, so as to the edge of images was extracted. The results showed that this method had high precision, and could be able to fully extract the edge of images. It is an effective method of extracting the edge of images.

Adaptive edge detection method for images

2008 ◽  
Vol 16 (1) ◽  
Author(s):  
A. Walczak ◽  
L. Puzio
Keyword(s):  
Edge Detection ◽  
Extraction Method ◽  
Detection Method ◽  
Polar Coordinate System ◽  
The Novel ◽  
Edge Extraction ◽  
Anisotropic Property ◽  
Multi Scale ◽  
Polar Coordinate ◽  
Edge Detection Method

AbstractThe novel two-dimensional (2D) wavelet with anisotropic property and application of it has been presented. Wavelet is constructed in the polar coordinate system to obtain anisotropic properties. A novel edge detection method has been developed with the aid of this wavelet. This method detects gradient jump and than follows along this jump. In this way the number of calculation for edge localization is reduced. Moreover, the presented method is able to detect all edges in an image in multi-scale together with its spatial orientation. Proposed wavelet as well as edge extraction method seems to be new way to edge detection for an image.

Adaptive and accurate color edge extraction method for one-shot shape acquisition

2016 ◽  
Vol 55 (9) ◽  
pp. 094104 ◽  
Author(s):  
Wei Yin ◽  
Xiaosheng Cheng ◽  
Haihua Cui ◽  
Dawei Li ◽  
Lei Zhou
Keyword(s):  
Extraction Method ◽  
Edge Extraction ◽  
Shape Acquisition
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