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基于视觉传达的模糊舰船图像目标分类检测
Fuzzy ship image target classification and detection based on visual communication
- DOI:
- 作者:
- 郭璟瑶
GUO Jing-yao
- 作者单位:
- 郑州科技学院, 河南 郑州 450064
Zhengzhou University of Science and Technology, Zhengzhou 450064, China
- 关键词:
- 视觉传达;模糊舰船图像;目标;分类检测
visual communication; blur ship images; objectives; classification detection
- 摘要:
- 模糊舰船图像的有效分类识别可提高对目标的准确打击和辨识能力,提出基于视觉传达和图像增强的模糊舰船图像目标分类检测模型。构建模糊舰船图像的多传感视觉采集模型,采用目标图像与背景图像差分分析方法实现对舰船图像的目标特征提取和聚类处理,根据视觉聚类传达和目标图像的特征点增强结果,结合模糊C均值聚类算法,实现对舰船目标图像的分类检测。测试得知,该方法进行舰船目标分类检测的聚类性较好,识别精度较高,视觉传达效果显著增强。
The effective classification and recognition of fuzzy ship images can improve the ability to accurately strike and identify targets. A fuzzy ship image target classification and detection model based on visual communication and image enhancement is proposed. Build a multi-sensor visual acquisition model for ship image, use the difference analysis method between target image and background image to extract and cluster the target features of the ship image. Communicate and enhance the feature points of the target image through visual clustering, and combine the fuzzy C-means clustering algorithm to achieve classification and detection of ship target images. The test shows that this method has good clustering performance, high recognition accuracy, and significantly enhanced visual communication effect for ship target classification and detection.
2023,45(9): 172-175 收稿日期:2023-01-06
DOI:10.3404/j.issn.1672-7649.2023.09.038
分类号:TP391
基金项目:河南省社科普及规划项目课题(0454)
作者简介:郭璟瑶(1984-),女,硕士,讲师,研究方向为视觉传达