Combination of Canny Edge Detection and Blob Processing Techniques for Shrimp Larvae Counting

被引:0
作者
Awalludin, E. A. [1 ]
Yaziz, Mat M. Y. [1 ]
Rahman, Abdul N. R. [1 ]
Yussof, W. N. J. H. W. [2 ]
Hitam, M. S. [2 ]
Arsad, T. T. N. [1 ]
机构
[1] Univ Malaysia Terengganu UMT, Sch Fisheries & Aquaculture Sci PPSPA, Kuala Nerus 21030, Malaysia
[2] Univ Malaysia Terengganu UMT, Sch Informat & Appl Math PPIMG, Kuala Nerus 21030, Malaysia
来源
PROCEEDINGS OF THE 2019 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING APPLICATIONS (IEEE ICSIPA 2019) | 2019年
关键词
image processing; image enhancement; image segmentation; blob analysis; shrimp larvae (Penaeus vannamei);
D O I
10.1109/icsipa45851.2019.8977746
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents the proposed method to count the number of the shrimp larvae using computer technology based approach. The high demand of computer aids in counting Shrimp larvae are required in calculating survival rate of Shrimp larvae. Currently, the process of handling shrimp from post to adult larvae stage is still conducted with a tedious and labor-intensive task especially in calculating the number of shrimp larvae. However, the use of the manual counting approach has suffered with some drawbacks such as inaccurate, time consuming, laborious, human intervention, sequential processes and over-estimation. Since that, many researchers are interested into this the fundamental research and development challenges. In this study, we present an image processing technique and blob analysis for counting the number of shrimp larvae. The use of image processing technique helps for object counting specifically on image enhancement and image segmentation. Meanwhile, a Blob analysis algorithm is used as connected component to find and count shrimp larvae in the image through the experiment. The performance of the proposed method is evaluated by comparing the results with the manual counting system using all ninety samples dataset. All ninety samples of shrimp larvae (Penaeus vannamei) were obtained from the Freshwater Hatchery of University Malaysia Terengganu. The experimental results demonstrate that the proposed method is outperformed compared to the manual counting approach through the experiment by reducing the analysis time with minimizing the sequential process task.
引用
收藏
页码:308 / 313
页数:6
相关论文
共 15 条
[1]  
Abu M., 2017, ARPN J ENG APPL SCI, V12
[3]   High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection [J].
Choudhry, Priya .
PLOS ONE, 2016, 11 (02)
[4]  
Forero M. G., 2011, ADV BIOMED ENG, P978
[5]   Conventionalized gestures for the interaction of people in traffic with autonomous vehicles [J].
Gupta, Surabhi ;
Vasardani, Maria ;
Winter, Stephan .
PROCEEDINGS OF THE 9TH ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON COMPUTATIONAL TRANSPORTATION SCIENCE (IWCTS 2016), 2016, :55-60
[6]  
Iscimen B., NATURAL ENG SCI, V2, P25
[7]  
Kim Sung, 2013, Ocean and Polar Research, V35, P239, DOI 10.4217/OPR.2013.35.3.239
[8]  
Konam S, 2014, 2014 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), P2464, DOI 10.1109/ICACCI.2014.6968534
[9]  
Loh B. C. S., 2011, Proceedings of the 2011 IEEE 9th International Conference on Dependable, Autonomic and Secure Computing (DASC 2011), P192, DOI 10.1109/DASC.2011.53
[10]   A framework for edge detection based on relief functions [J].
Lopez-Molina, C. ;
De Baets, B. ;
Bustince, H. .
INFORMATION SCIENCES, 2014, 278 :127-140