An improved high-accuracy centroid detection method for Shack-Hartmann wavefront sensor

Author(s):  
Suiting He ◽  
Feng Shen
2010 ◽  
Vol 09 (03) ◽  
pp. 123-133
Author(s):  
XIAOMING YIN ◽  
LIPING ZHAO ◽  
XIANG LI ◽  
ZHONGPING FANG

Shack–Hartmann wavefront sensor splits the incident wavefront into many subsections and transfers the distorted wavefront detection into the centroid measurement. The accuracy of the centroid measurement determines the accuracy of the SHWS. In this paper, we have presented an automatic centroid measurement method based on the image processing technology for practical applications of the digital SHWS in surface profile measurement. The method can detect the centroid of each focal spot accurately and robustly by eliminating the influences of various noises. Based on this centroid detection method, we have developed a digital SHWS system which can automatically detect centroids of focal spots, reconstruct the wavefront, and measure the 3D profile of the surface. The experimental results demonstrate that the system has good accuracy, repeatability and compatibility to optical misalignment. The system is suitable for online applications of surface measurement.


2015 ◽  
Vol 41 (12) ◽  
pp. 3120-3130 ◽  
Author(s):  
Koichi Ito ◽  
Kazumasa Noro ◽  
Yukari Yanagisawa ◽  
Maya Sakamoto ◽  
Shiro Mori ◽  
...  

2009 ◽  
Vol 29 (12) ◽  
pp. 3385-3390 ◽  
Author(s):  
郑翰清 Zheng Hanqing ◽  
饶长辉 Rao Changhui ◽  
饶学军 Rao Xuejun ◽  
姜文汉 Jiang Wenhan ◽  
杨金生 Yang Jinsheng

2017 ◽  
Vol 9 (32) ◽  
pp. 4695-4701 ◽  
Author(s):  
Xiaodan Wang ◽  
Hongmei Wang ◽  
Yingming Cai ◽  
Jiahui Jin ◽  
Lingtao Zhu ◽  
...  

A novel method using bionic mastication system based on a pressure sensor was developed to predict beef tenderness with convenience, stability and high accuracy. What's more, this method can be applied to detect other meat tenderness such as those of chicken and pork as well, which indicates a universality of this method.


2014 ◽  
Vol 641-642 ◽  
pp. 1275-1279 ◽  
Author(s):  
Xiao Jun He ◽  
Zhen Di Yi ◽  
Jing Liu ◽  
Yu Zheng Wang

In order to reach and test the surface defects on industrial parts, based on Machine Vision this paper put forward a defective parts detection method. The method of median filter was adopted to eliminate the noise of image. The Ostu-method was used for the segmenting threshold. Pixel level and level edge detection were used to complete the precise components defects detection. Experiments show that this scheme is feasible, and can achieve high accuracy and shorter testing time.


Author(s):  
Anindita Suryarasmi ◽  
Reza Pulungan

AbstrakNotasi musik merupakan dokumentasi tertulis dari sebuah lagu. Walaupun notasi musik telah umum digunakan, namun tidak semua orang yang berkecimpung di dalam dunia musik memahami bagaimana notasi musik dituliskan. Penelitian ini menawarkan penyusunan notasi music secara otomatis dengan mengimplementasikan metode onset detection. Hal mendasar yang harus diketahui dalam pembuatan notasi musik adalah durasi serta nada yang dimainkan. Dengan menggunakan mendeteksi onset dari data audio, jarak antar pukulan dapat diketahui. Dengan demikian maka durasi permainan pun bisa dihitung. Hasil dari pencarian durasi tersebut diolah kembali untuk menciptakan objek-objek note yang disusun dalam notasi musik. Sistem menghasilkan keluaran berupa file dengan format musicXML. Dengan format ini maka hasil keluaran sistem akan bersifat dinamis dan dapat diolah kembali dengan music editor yang mendukung format file tersebut.Hasil penelitian menunjukkan akurasi yang tinggi dalam pengenalan pola permainan yang berhubungan dengan durasi setiap note hingga mencapai 99.62%.  Kata kunci— notasi musik, onset detection, musicXML  AbstractMusical notation is written documentation of a music. Even though musical notation is commonly used, not every musician knows how to write a musical notation. This work offers automatic musical notation generation from audio signal using onset detection.Duration and pitch of the notes are two basic parameters that have to be known in order to generate music notation. This work implemented onset detection method to recognize the pattern by measuring the interval between two notes. Using the interval, the duration of each notes can be calculated and used to create note objects in order to arrange a musical notation. The output of the system is a musicXML formatted file. This format allowed the output to be edited using software for music editor. The result of this work shows high accuracy up to 99.62% for detecting each notes and measuring the duration. Keywords— musical notation, onset detection, musicXML


Author(s):  
Jun Shimokawatoko ◽  
Hiroyuki Mizutani ◽  
Ken'ichi Tajima ◽  
Mori Kazutomi

Sign in / Sign up

Export Citation Format

Share Document