Although the development of the robot picking vision system is widely applied,it is very challenging for fruit detection in orchards with complex light and environment,especially for fruit colors similar to the backgr...Although the development of the robot picking vision system is widely applied,it is very challenging for fruit detection in orchards with complex light and environment,especially for fruit colors similar to the background.In recent,there are few studies on pecan fruit detection and location based on machine vision.In this study,an accurate and efficient pecan fruit detection method was proposed based on machine vision under natural pecan orchards.In order to solve the illumination problem,a light compensation algorithm was first utilized to process the collected samples,and then an improved Faster Region Convolutional Neural Network(Faster RCNN)with the Feature Pyramid Networks(FPN)was established to train the samples.Finally,the pecan number counting method was introduced to count the number of pecan.A total of 241 pecan images were tested,and comparison experiments were carried out.The mean average precision(mAP)of the proposed detection method was 95.932%,compared with the result without uneven illumination correction(UIC),which was increased by 0.849%,while the mAP of the Single Shot Detector(SSD)+FPN was 92.991%.In addition,the number of clusters was counted using the proposed method with an accuracy rate of 93.539%compared with the actual clusters.The results demonstrate that the proposed network has good robustness for pecan fruit detection in different illumination and various unstructured environments,and the experimental achievement has great potential for robot-picking visual systems.展开更多
We propose a two-cascaded, constant-resistance, symmetrical bridged-T amplitude equalizer for a high-speed visible light communication(VLC) system. With the pre-equalization circuit, the-3 d B bandwidth of the VLC s...We propose a two-cascaded, constant-resistance, symmetrical bridged-T amplitude equalizer for a high-speed visible light communication(VLC) system. With the pre-equalization circuit, the-3 d B bandwidth of the VLC system can be extended from 12 to 235 MHz using a commercially available phosphorescent white light-emitting diode(LED), a blue filter, and a low-cost PIN photodiode. The data rate is 1.20 Gbit/s, exploiting 16-quadrature amplitude modulation-orthogonal frequency-division multiplexing with a 300 MHz modulation bandwidth over50 cm of free-space transmission under the pre-forward error correction limit of 3.8 × 10^-3. To our knowledge,this is the highest-3 d B bandwidth and the highest data rate ever achieved by using a pre-equalization circuit and white LED in a VLC system.展开更多
基金funded by the Forestry Science and Technology Innovation Fund Project of Hunan Province(Grant No.XLK202108-4)and the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Although the development of the robot picking vision system is widely applied,it is very challenging for fruit detection in orchards with complex light and environment,especially for fruit colors similar to the background.In recent,there are few studies on pecan fruit detection and location based on machine vision.In this study,an accurate and efficient pecan fruit detection method was proposed based on machine vision under natural pecan orchards.In order to solve the illumination problem,a light compensation algorithm was first utilized to process the collected samples,and then an improved Faster Region Convolutional Neural Network(Faster RCNN)with the Feature Pyramid Networks(FPN)was established to train the samples.Finally,the pecan number counting method was introduced to count the number of pecan.A total of 241 pecan images were tested,and comparison experiments were carried out.The mean average precision(mAP)of the proposed detection method was 95.932%,compared with the result without uneven illumination correction(UIC),which was increased by 0.849%,while the mAP of the Single Shot Detector(SSD)+FPN was 92.991%.In addition,the number of clusters was counted using the proposed method with an accuracy rate of 93.539%compared with the actual clusters.The results demonstrate that the proposed network has good robustness for pecan fruit detection in different illumination and various unstructured environments,and the experimental achievement has great potential for robot-picking visual systems.
基金supported by the National Natural Science Foundation of China (No. 61177071)the National "863" Program of China (No. 2013AA013603)
文摘We propose a two-cascaded, constant-resistance, symmetrical bridged-T amplitude equalizer for a high-speed visible light communication(VLC) system. With the pre-equalization circuit, the-3 d B bandwidth of the VLC system can be extended from 12 to 235 MHz using a commercially available phosphorescent white light-emitting diode(LED), a blue filter, and a low-cost PIN photodiode. The data rate is 1.20 Gbit/s, exploiting 16-quadrature amplitude modulation-orthogonal frequency-division multiplexing with a 300 MHz modulation bandwidth over50 cm of free-space transmission under the pre-forward error correction limit of 3.8 × 10^-3. To our knowledge,this is the highest-3 d B bandwidth and the highest data rate ever achieved by using a pre-equalization circuit and white LED in a VLC system.