Study on the Image Segmentation Algorithm with Depth Data of Kinect

2014 ◽  
Vol 998-999 ◽  
pp. 929-933
Author(s):  
Lu Yi Li ◽  
Jun Yong Ye
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Surface Area ◽  
Segmentation Algorithm ◽  
Detection Methods ◽  
Depth Image ◽  
Normal Vector ◽  
Support Surface ◽  
Canny Operator ◽  
Depth Data

In the segmentation algorithms of the depth image, because the object and its support surface are continuous in the depth data ,the traditional method of edge detection methods can’t detect the edge between the object and its support surface. To solve this problem, the segmentation algorithm of the depth image is studied in this paper. Firstly, we use canny operator to detect the edge the of depth image of the scene. Then the depth image of the scene is transformed into points of a 3-D space coordinate and normal vector is calculated for each point. The method of calculation the direction of the normal vector is used to determine the point of which belongs to the support surface area, which determine the support surface area of the scene. Finally, we detect image edge of the image that the support surface area is extracted, and fuse the result of canny operator edge detection and edge of the image that the support surface area is extracted. Experiments show that the segmentation algorithm works well, which the problem of detection the edge between the support surface area and the object and can also achieve a good depth image segmentation.

A Study on Different Edge Detection Techniques in Digital Image Processing

2017 ◽  
pp. 100-122 ◽  
Author(s):  
Shouvik Chakraborty ◽  
Mousomi Roy ◽  
Sirshendu Hore
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Basic Feature ◽  
Detection Methods ◽  
Natural Image ◽  
Detection Techniques ◽  
Image Edges

Image segmentation is one of the fundamental problems in image processing. In digital image processing, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge is a one of the basic feature of an image. Edge detection can be used as a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. The image edges include a good number of rich information that is very significant for obtaining the image characteristic by object recognition and analyzing the image. In a gray scale image, the edge is a local feature that, within a neighborhood, separates two regions, in each of which the gray level is more or less uniform with different values on the two sides of the edge. In this paper, the main objective is to study the theory of edge detection for image segmentation using various computing approaches.

Extracting Golden Area from Image Based on Canny Operator

2015 ◽  
Vol 731 ◽  
pp. 201-204
Author(s):  
Ying Wu ◽  
Xiu Ping Zhao ◽  
Yang Jin ◽  
Xi Zhang
Keyword(s):  
Image Segmentation ◽  
Color Space ◽  
Threshold Value ◽  
Segmentation Algorithm ◽  
Canny Operator ◽  
Small Areas ◽  
Color Separation ◽  
Lab Color Space ◽  
Canny Algorithm ◽  
Image Segmentation Algorithm

This paper researched application of Canny algorithm on the color separation of golden image , to generate a separated golden image plate base on the extraction of golden area, so as to get the effect more closer to the real metallic. Canny algorithm is based on the gray-scale image segmentation algorithm. The image is mapped from RGB to Lab color space. According to the color attributes of b, the golden target regions are extracted using Canny algorithm. But it’s difficult to get the closed target boundary outlet by Canny algorithm, so this paper modified image segmentation algorithm. Firstly, the image is filtered by Canny operator; secondly, small areas on the Canny processed image are removed by using some pre-determined threshold value.; then processed the image through using smoothing and sharping method so to make inner area of image more smooth meanwhile improving boundary sharpness. The experimental results showed that the method based on Canny operator is very suitable for golden area extraction from a image. The golden target-regions can be closed boundary outlet, which makes the golden areas are more accurate and continuous.

scholarly journals Performance comparison of segmentation algorithms for hand gesture recognition

2018 ◽  
Vol 7 (3) ◽  
pp. 1227
Author(s):  
Priyanka Parvathy D ◽  
Dr Kamalraj Subramaniam
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Gesture Recognition ◽  
Noise Removal ◽  
Hand Gesture Recognition ◽  
Segmentation Algorithm ◽  
Hand Gesture ◽  
Canny Edge Detection ◽  
Canny Edge ◽  
Image Segmentation Algorithm

The gestures presented in diverse backgrounds have to be accurately processed and segmented, for it to be classified precisely by the hand gesture recognition system. This study compares performance of the proposed Image Segmentation Algorithm with a standard Canny Edge Detection Algorithm by comparing the statistical values of the features obtained from the feature extraction stage, thus validating the importance of having a robust preprocessing stage for the hand gestures. The proposed algorithm uses Non-local Mean filter for noise removal and then an improved Global Swarm Optimization based Canny edge detection for extracting the edges. Features are extracted using two dimensional Multi-resolution Discrete Wavelet Transform (2D-DWT) combined with Gray-level Co-occurrence Matrix. The efficiency of the proposed Image Segmentation Algorithm is evaluated using Radial Basis Function Neural Network as the classifier.  

A hybrid image segmentation algorithm based on edge detection, thresholding and region growing

2007 ◽  
Author(s):  
Zhiming Xie ◽  
Guannan Chen ◽  
Rong Chen ◽  
Jinping Lei ◽  
Shangyuan Feng ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Region Growing ◽  
Segmentation Algorithm ◽  
Image Segmentation Algorithm
Sign in / Sign up

Export Citation Format

Share Document