Title :
Cotton top feature identification based on machine vision&image processing
Author :
Wang, Weixin ; Qu, Duanyang ; Ma, Benxue ; Wang, Yage
Author_Institution :
Coll. of Mech. & Electron. Eng, Shi hezi Univ., Shi hezi, China
Abstract :
Extracting cotton top features for cotton top identification and location based on machine vision & image processing is explored in this paper. We have implemented three different color spaces namely Ycbcr color space, HSI color space, and YIQ color space for extracting cotton top feature from cotton plant images. The Area of the regions is extracted as cotton top feature in this paper. Huge database of images have been used to test the results in different color space models. The paper also shows the comparison of the results obtained by implementing in different color space models. The comparison of the results showed good accuracy in different color space models. Ycbcr color space is considered as the best color space model for extracting cotton top in this paper.
Keywords :
botany; computer vision; feature extraction; image colour analysis; visual databases; HSI color space; YIQ color space; Ycbcr color space; color space model; cotton plant image; cotton top extraction; cotton top feature identification; image database; image processing; machine vision; Biological system modeling; Cotton; Feature extraction; Image color analysis; Image segmentation; Machine vision; HSI color space; YIQ color space; Ycbcr color space; algorithms; cotton top feature; extracted; image processing; machine vision;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
DOI :
10.1109/CSAE.2011.5953309