Open Journal Systems

Construction of ship target image library based on 3DS MAX and AP algorithm

Ji Chao(Department of Navigation and Communication, Navy Submarine Academy, QingDao, China)
Xia Wei xing(Department of Navigation and Communication, Navy Submarine Academy, QingDao, China)
Tang Zheng ping(Department of Navigation and Communication, Navy Submarine Academy, QingDao, China)


To achieve accurate classification and recognition of ship target types, it is necessary to establish a sample library of ship targets to be identified. On the basis of exploring the principles of building a ship target image library, the paper determines the sample set. Using 3DS MAX software as the platform, combined with the accurate 3D model of the ship in offline state, the software fully utilizes its own rendering and animation functions to achieve automatic generation of multi view and multi scale views of ship targets. To reduce the storage capacity of the image database, a construction method of the ship target image database based on AP algorithm is presented. The algorithm can obtain the optimal cluster number, reduce the data storage capacity of the image database, and save the calculation amount for the subsequent matching calculation.


et Image Li AP algorithm. Ship Targbrary. 3DS MAX. Image recognition


YANG Lei. Application of Computer Intelligent Image Recognition Technology, Electronic Technology[J], 2023,56(6):298-300.

Li Linyang, Li Gaoming, Li Xiao. Research on Semi Supervised Neighborhood Propagation Clustering Integration Algorithm, China Computer & Communication[J], 2020:49-51.

ZHOU Shu-qiang, GENG Rui-huan. Research on the ship target image feature recognition system,SHIP SCIENCE AND TECHNOLOGY[J], 2023,45(5):182-185.

LIU Yuan, GU Yin. Application of image recognition technology based on OpenCV in Collision Avoidance of Unmanned Craft, Journal of Military Transportation, 2022,1(8):92-94.

LU Wei. Computer Vision Bayberry Fruit Image Recognition Based on K-means Clustering, Modern Computer[J], 2022,28(8):78-80.

LI guang-ming,YU Jian, ZHANG Haitao. Improvement of affinity propagation clustering and its application in competitive intelligence. Journal of Nanjing University of Science and Technology[J], 2022,46(2):192-197.

DUAN Gui-qin, ZOU Chen-song. Occupational Competence Evaluation Model Based on Affinity Propagation Clustering. Computer and Modernization[J], 2022,5:22-27.

SMINESH CN, KANAGAE, SREEJISH AG. Augmented Affinity Propagation-Based Network Partitioning for Multiple Controllers Placementin Software Defined Networks[J]. Journal of Computational and Theoretical Nanoscience,2020,17(1): 228-233.



  • There are currently no refbacks.
Copyright © 2023 Ji Chao, Xia Wei xing, Tang Zheng ping Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
  • :+65-62233778 QQ:2249355960