A New Image Segmentation Algorithm and Its Application in Lettuce Object Segmentation

Jun Sun Jun Sun, Yan Wang Yan Wang, Xiaohong Wu Xiaohong Wu, Xiaodong Zhang, Hongyan Gao

Abstract


Lettuce image segmentation which based on computer image processing is the premise of non-destructive testing of lettuce quality. The traditional 2-D maximum entropy algorithm has some faults, such as low accuracy of segmentation, slow speed, and poor anti-noise ability. As a result, it leads to the problems of poor image segmentation and low efficiency. An improved 2-D maximum entropy algorithm is presented in this paper. It redistricts segmented regions and furtherly classifies the segmented image pixels with the method of the minimum fuzzy entropy, and reduces the impact of noise points, as a result the image segmentation accuracy is improved. The improved algorithm is used to lettuce object segmentation, and the experimental results show that the improved segmentation algorithm has many advantages compared with the traditional 2-D maximum entropy algorithm, such as less false interference, strong anti-noise ability, good robustness and validity.

Full Text:

PDF

References


S Yuhuan, Y Zhihai. Research Progress in Diagnosis Methods of Rice Nitrogen Nutrition. Journal of Anhui Agricultural Sciences. 2008; 19( 36).

Siti Nurmaini, Bambang Tutuko. A New Classification Technique in Mobile Robot Navigation.TELKOMNIKA Indonesian Journal of Electrical Engineering. 2011; 9(3).

Arif Muntasa, Indah Agustien Sirajudin, Mauridhi Hery Purnomo. Appearance Global and Local Structure Fusion for Face Image Recognition. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2011; 9(1).

Y Yibin, Y Haiyan. The research progress of agricultural products quality nondestructive testing technique. Chinese Society of Agricultural Engineering Annual Conference. Beijing, China. Dec 2005: 70-83.

C Yu, C Dianren, L Yang, C Lei. Otsu’s Thresholding Method Based on Gray Level-Gradient Two-Dimensional Histogram. Informatics in Control, Automation and Robotics (CAR). Changchun, China. March 2010: 282-285.

T Zhao-xia. Image Segmentation Algorithm based on Improved GA and OTSU. Jilin Normal University Journal (Natural Science Edition). 2011; 2( 5).

Helen R, Kamaraj N , Selvi K, Raja Raman V. Segmentation of pulmonary parenchyma in CT lung images based on 2D Otsu optimized by PSO. Emerging Trends in Electrical and Computer Technology (ICETECT). Madurai, India. March 2011: 536-541.

X Ruohui. An Image Segmentation Algorithm using Genetic Strategy. Computer Engineering and Technology (ICCET). Wenzhou, China. April 2010: 605-607.

Z Chaoquan, L Jiansheng, Z Weigang. Robust Image Segmentation Algorithm Based On Rough Sets and Fuzzy C-Means. Information Science and Engineering (ISISE). Ganzhou, China. Dec 2010: 411-484.

X Rong, Ohya, Jun. An improved Kernel-based Fuzzy C-means Algorithm with spatial information for brain MR image segmentation. Tokyo, Japan. Nov 2010: 1-7.

W Wenyuan, W Fangmei. Maximum Entropy Method of Image Segmentation Based on Genetic Algorithm. Computer Simulation. 2011; 8: 28.

L Xiujuan, Fu Ali. 2-D Maximum-entropy Thresholding Image Segmentation Method Based on Second-order Oscillating PSO. Natural Computation. Xi’an, China. Aug 2009: 161- 165.

L Guihai, H Wenming, L Song. 2-D Maximum Entropy Spermatozoa Image Segmentation Based on Canny Operator. Intelligent Computing and Integrated Systems (ICISS). Guilin, China. Oct 2010: 243-246.

Z. Lufang, G. Leye. 2-D maximum entropy method in image segmentation based on genetic quantum algorithm. Computer Applications. 2005; 8: 25.

Z.Feng, F.Jiulun. One Image Segmentation Method Combining 2D Otsu’s Method and Fuzzy Entropy. Application Research of Computers. 2007; 6:24.




DOI: http://dx.doi.org/10.12928/telkomnika.v10i3.837

Article Metrics

Abstract view : 118 times
PDF - 125 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2014 Universitas Ahmad Dahlan

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

View TELKOMNIKA Stats