水产学报2024，Vol.48Issue(12)：61-71,11.DOI:10.11964/jfc.20201212549
基于计算机视觉的鱼类形态轮廓特征自动提取
Automatic extraction of contour features of fish morphology based on computer vision
摘要
Abstract
With the rapid development of artificial intelligence,modern fish biology research technology has been constantly updated.Automated and intelligent fish identification will help promote modern fish biology research development.The contour feature of fish morphology is one of the important features of fish recognition.Fish morphology is diversed,and the contour features of fish morphology have species specificity.Meanwhile,it serves as an important scientific basis for fish identification and classification.The extraction effects of morphological contour features directly affect the accuracy of automatic fish identification.Therefore,in order to study the effect of computer vision on the automatic extraction of fish morphological contour features,a two-dimensional image of one tail T.obesus was collected in the Pacific Ocean from September to November 2017 for computer vision ana-lysis through the fish image gray level transformation,bilateral filter,binary image processing and contour extrac-tion and other image processing.8-direction chain code technology was used to automatically extract the chain code information of fish contour.The morphological information coefficient was calculated by elliptic Fourier transform and the contour reconstruction was carried out.The results revealed that the contour image of tuna could be obtained well after processing,and the chain code information changes with the size of the contour pixel of fish shape,and the contour reconstruction of fish shape changed with the change of harmonic number.The research results showed that the automatic extraction of fish contour features was effective.The morphological coefficients of fish fluctuated greatly in low harmonic number and little in high harmonic number.The low harmonic number transformation had a great influence on the overall contour information of fish,while the high harmonic number transformation had a great influence on the local contour information of fish.The results of this study lay a prelim-inary foundation for automatic fish recognition and classification,and also provide references for other related automation research.关键词
鱼类/计算机视觉/形态轮廓/链码/形态系数/轮廓重建/自动提取Key words
fishes/computer vision/morphological contour/chain code/morphological coefficient/contour recon-struction/automatic extraction分类
农业科技引用本文复制引用
欧利国,蓝振峰,刘必林,陈新军,陈勇..基于计算机视觉的鱼类形态轮廓特征自动提取[J].水产学报,2024,48(12):61-71,11.基金项目
国家重点研发计划(2019YFD0901404) （2019YFD0901404）
国家自然科学基金(41876141) （41876141）
上海市高校特聘教授"东方学者"岗位计划(0810000243) （0810000243）
农业农村部西北太平洋公海渔业资源综合科学调查专项(D-8021-21-0109-01) （D-8021-21-0109-01）
上海市科技创新行动计划(19DZ1207502) National Key R&D Program of China(2019YFDO901404) （19DZ1207502）
National Natural Science Found-ation of China(41876141) （41876141）
Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institu-tions of Higher Learning under Contract(0810000243) （Eastern Scholar）
Ministry of Agriculture and Rural Affairs Major Program of Fisheries Resource Scientific Survey in the Northwest Pacific Ocean(D-8021-21-0109-01) （D-8021-21-0109-01）
Shanghai Science and Technology Innovation Action Plan(19DZ1207502) （19DZ1207502）
