[1]张 艺,匡 毅,王 梅,等.基于 OpenCV 的人体轮廓检测算法[J].计算机技术与发展,2020,30(08):81-85.[doi:10. 3969 / j. issn. 1673-629X. 2020. 08. 013]
　ZHANG Yi,KUANG Yi,WANG Mei,et al.Human Contour Detection Algorithm Based on OpenCV[J].,2020,30(08):81-85.[doi:10. 3969 / j. issn. 1673-629X. 2020. 08. 013]
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基于 OpenCV 的人体轮廓检测算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年08期
页码:
81-85
栏目:
智能、算法、系统工程
出版日期:
2020-08-10

文章信息/Info

Title:
Human Contour Detection Algorithm Based on OpenCV
文章编号:
1673-629X(2020)08-0081-05
作者:
张 艺; 匡 毅; 王 梅; 黄志远; 胡 松
成都理工大学 信息科学与技术学院,四川 成都 610059
Author(s):
ZHANG Yi; KUANG Yi; WANG Mei; HUANG Zhi-yuan; HU Song
School of Information Science and Technology,Chengdu University of Technology,Chengdu 610059,China
关键词:
OpenCV; 图像处理; 高斯滤波; Sobel 检测算子; 轮廓检测
Keywords:
OpenCV; image processing; Gaussian filtering; Sobel edge detection operator; contour detection
分类号:
P301. 6
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 08. 013
摘要:
人体轮廓检测一直都是图像处理领域研究的热点问题,在监控系统、军事扫描搜寻、无人驾驶以及机场的安全等方面都有着息息相关的应用。 针对目前在地下停车场或者机场等不方便进行人工监督的地方,为了保障行人安全,提出了一种基于 OpenCV 的人体轮廓检测研究方法。 对所标记和存储的人体图像进行去噪和图像形态学处理,通过 Canny 边缘检测和膨胀及腐蚀处理,以阈值化等方法得到图像轮廓。 同时对于人体轮廓的边缘检测,选用最优的 Sobel 算子作为边缘检测算子;然后从图像中检索并绘制出人体轮廓,把人体区域提取出来并保存。 通过实验证明,提出算法的平均人体轮廓检测正确率为 91.7% ,除了准确性,该方法的运算时间与中值滤波相比,缩短了 80%。 因此,该方法既能够保证人体检测的准确性,又能够实现快速检测,在机场等人流量大,检测不便的应用场合具有较强的适用性。
Abstract:
Human contour detection has always been a hot issue in the field of image processing,and it has closely related applications in monitoring systems, military scanning search,unmanned driving and airport security. In order to ensure the safety of pedestrians in places where it is not convenient to carry out manual supervision in underground parking lots or airports,we propose a human contour detection method based on OpenCV. The labeled and stored human images are denoised and morphologically processed. Through Canny edge detection and expansion and erosion processing, image contours are obtained by thresholding methods. At the same time,the optimal Sobel operator is selected as the edge detection operator for human body contour,and then the human body contour is retrieved from the image and drawn, and the human body region is extracted and saved. Experiment shows that the average human contour detection accuracy of the algorithm is 91. 7% . In addition to accuracy, its calcu-lation time is shortened by 80% compared with the median filtering. Therefore,the proposed method can not only ensure the accuracy of human body detection, but also achieve rapid detection,which has strong applicability in airports and other applications where the human flow is large and the detection is inconvenient.

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更新日期/Last Update: 2020-08-10