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 analysis through the fish image gray level transformation, bilateral filter, binary image processing and contour extraction 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 preliminary foundation for automatic fish recognition and classification, and also provide references for other related automation research.