Garden Visitor Detection Based on Improved Vibe Algorithm

2021 ◽  
pp. 100-106
Author(s):  
Zhiheng Shu
Keyword(s):  
Vibe Algorithm

scholarly journals Trichomonas Detection in Leucorrhea Based on VIBE Method

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Xiaohui Du ◽  
Lin Liu ◽  
Xiangzhou Wang ◽  
Jing Zhang ◽  
Guangming Ni ◽  
...  
Keyword(s):  
Detection System ◽  
Ground Truth ◽  
Correct Classification ◽  
Improved Method ◽  
False Detection ◽  
Still Images ◽  
Model Update ◽  
Motion Characteristic ◽  
Automatic Detection System ◽  
Vibe Algorithm

Trichomonas examination is one of the important items in the leucorrhea routine detection. And it cannot be recognized by still images because of the unstable morphology and unfixed focal location caused by motion characteristic. We proposed an improved VIBE algorithm. 6 videos (totally 1414 frames) are collected for testing. In order to compare the effects of the algorithms, we segment each frame artificially as ground truth. Experiments show that percentage of correct classification (PCC) achieves 88%. The proposed improved method can effectively suppress the false detection caused by the formed components such as epithelial cells in the leucorrhea microscopic image and the missed detection caused by the background model update during the movement. At the same time, improvements can effectively suppress smear and ghost areas. The algorithm proposed in this paper can be integrated into the leucorrhea automatic detection system.

Fusing Canny operator with vibe algorithm for target detection

2016 ◽  
Author(s):  
Dongliang Jin ◽  
Songhao Zhu ◽  
Xian Sun ◽  
Zhiwei Liang ◽  
Guozheng Xu
Keyword(s):  
Target Detection ◽  
Canny Operator ◽  
Vibe Algorithm

scholarly journals Improved Adaptive Vibe and the Application for Segmentation of Complex Background

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Le Chang ◽  
Zhenghua Liu ◽  
Yan Ren
Keyword(s):  
Background Noise ◽  
Adaptive Threshold ◽  
Complex Environment ◽  
Basic Algorithm ◽  
Complex Background ◽  
Texture Characteristics ◽  
Improvement Measures ◽  
Threshold Setting ◽  
Computing Speed ◽  
Vibe Algorithm

To solve the problems that basic Vibe algorithm cannot effectively eliminate the influence of background noise, follower shadow, and ghost under complex background effectively, an adaptive threshold algorithm, AdaVibe, based on the framework of basic Vibe is proposed. Aiming at the shortage of the basic algorithm, this paper puts forward some improvement measures in threshold setting, shadow eliminating, and ghost suppression. Firstly, judgment threshold takes adjustment with the changes of background. Secondly, a fast eliminating ghost algorithm depending on adaptive threshold is introduced. Finally, follower shadow is detected and inhibited effectively through the gray properties and texture characteristics. Experiments show that the proposed AdaVibe algorithm works well in complex environment without affecting computing speed and has stronger robustness and better adaptability than the basic algorithm. Meanwhile, the ghost and follower shadow can be absorbed quickly as well. Therefore, the accuracy of target detection is effectively improved.

Verification of AIS Data by using Video Images taken by a UAV

2019 ◽  
Vol 72 (06) ◽  
pp. 1345-1358 ◽  
Author(s):  
Fan Zhou ◽  
Shengda Pan ◽  
Jingjing Jiang
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Target Image ◽  
Inland Waterways ◽  
Safe Navigation ◽  
Traffic Regulation ◽  
Video Images ◽  
Aerial Vehicle ◽  
Positioning Algorithm ◽  
Vibe Algorithm

Effective technical methods for verifying the authenticity and accuracy of Automatic Identification System (AIS) data, which are important for safe navigation and traffic regulation, are still lacking. In this study, we propose a new method to verify AIS data by using video images taken by an Unmanned Aerial Vehicle (UAV). An improved ViBe algorithm is used to extract the ship target image from the video images and the ship's spatial position is calculated using a monocular target-positioning algorithm. The positioning results are compared with the position, speed and course data of the same ship in AIS, and the authenticity and accuracy of the AIS data are verified. The results of the experiment conducted in the inland waterways of Huangpu River in Shanghai, China, show that AIS signals can be automatically checked and verified by a UAV in real time and can thus improve the supervision efficiency of maritime departments.

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