A key frame extraction method for processing greenhouse vegetables production monitoring video

作者：Ma Juncheng; Li Xinxing; Wen Haojie; Fu Zetian; Zhang Lingxian^*

来源：Computers and Electronics in Agriculture, 2015, 111: 92-102.

DOI：10.1016/j.compag.2014.12.007

• Greenhouse vegetables
• Monitoring video
• Key frames
• Visual saliency
• On line clustering
• Mean pixels value

Research reported in this paper aims to improve the identification of greenhouse vegetable diseases based on the greenhouse monitoring video. It presents a method that combines the visual saliency and online clustering to extract the key frame from greenhouse vegetables monitoring video. Firstly X-2 histograms are used to measure the similarity of each frame to the first frame, which eliminates the meaningless frames and improve data processing efficiency and costs. Then, all frames will be converted to HSV color space and a saliency map of each frame is generated based on H component value and S component value. According to the saliency map, the salient region can be obtained. During the process of extracting the salient region, there is a possibility that the information of disease spots is lost. Therefore, morphological method would be utilized to restore the lost information. Finally, online clustering is performed to classify the salient regions into different clusters, and mean pixels value is used to select the key frames. The results indicate that this method can obtain information of entire leaf area of vegetables and extract the key frame effectively.

• 出版日期2015-2
• 单位中国农业大学