遮蔽检测是真正射影像生成的关键技术。提出一种基于多边形反演成像(polygon based inversion imaging,PBI)的遮蔽检测方法。利用建筑物表面多边形内部互不遮蔽的特点,以多边形为单元将建筑物逆投影到像方,反演成像时的目标状态,获得目...遮蔽检测是真正射影像生成的关键技术。提出一种基于多边形反演成像(polygon based inversion imaging,PBI)的遮蔽检测方法。利用建筑物表面多边形内部互不遮蔽的特点,以多边形为单元将建筑物逆投影到像方,反演成像时的目标状态,获得目标之间、多边形之间的遮蔽关系。为确保算法的稳健性和保真度,提出:①可疑区域增长法,稳健地栅格化复杂3维建筑物模型;②综合滤波模型用于消除多边形边界噪声。最后利用实例比较z-buffer方法,基于射线角度方法和PBI方法的遮蔽检测效果。结果表明,PBI算法的有效性和稳健性较好。展开更多
Visible light communications(VLC) have recently attracted a growing interest and can be a potential solution to realize indoor positioning,however,the performance of existing indoor positioning system is limited by mu...Visible light communications(VLC) have recently attracted a growing interest and can be a potential solution to realize indoor positioning,however,the performance of existing indoor positioning system is limited by multipath distortion inside a room.In order to combat the effect of multipath distortion,this paper proposes an LED-based indoor positioning algorithm combined with hybrid OFDM(HOFDM),in which asymmetrically clipped optical OFDM(ACOOFDM) is transmitted on the odd subcarriers while using pulse amplitude modulated discrete multitone(PAM-DMT) to modulate the imaginary part of each even subcarrier.In this scheme,we take a combined approach where a received-signal-strength(RSS) technique is employed to determine the location of the receiver and realize the 3-D positioning by Trust-region-based positioning.Moreover,a particle filter is used to further improve the positioning accuracy.Results confirm that this proposed positioning algorithm can achieve high accuracy even with multipath distortion,and the algorithm has better performance when combined with particle filter.展开更多
Hand gestures are powerful means of communication among humans and sign language is the most natural and expressive way of communication for dump and deaf people. In this work, real-time hand gesture system is propose...Hand gestures are powerful means of communication among humans and sign language is the most natural and expressive way of communication for dump and deaf people. In this work, real-time hand gesture system is proposed. Experimental setup of the system uses fixed position low-cost web camera with 10 mega pixel resolution mounted on the top of monitor of computer which captures snapshot using Red Green Blue [RGB] color space from fixed distance. This work is divided into four stages such as image preprocessing, region extraction, feature extraction, feature matching. First stage converts captured RGB image into binary image using gray threshold method with noise removed using median filter [medfilt2] and Guassian filter, followed by morphological operations. Second stage extracts hand region using blob and crop is applied for getting region of interest and then “Sobel” edge detection is applied on extracted region. Third stage produces feature vector as centroid and area of edge, which will be compared with feature vectors of a training dataset of gestures using Euclidian distance in the fourth stage. Least Euclidian distance gives recognition of perfect matching gesture for display of ASL alphabet, meaningful words using file handling. This paper includes experiments for 26 static hand gestures related to A-Z alphabets. Training dataset consists of 100 samples of each ASL symbol in different lightning conditions, different sizes and shapes of hand. This gesture recognition system can reliably recognize single-hand gestures in real time and can achieve a 90.19% recognition rate in complex background with a “minimum-possible constraints” approach.展开更多
The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve auto...The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve autonomous navigation in orchard,a visual navigation method based on multiple images at different shooting angles is proposed in this paper.A dynamic image capturing device is designed for camera installation and multiple images can be shot at different angles.Firstly,the obtained orchard images are classified into sky and soil detection stage.Each image is transformed to HSV space and initially segmented into sky,canopy and soil regions by median filtering and morphological processing.Secondly,the sky and soil regions are extracted by the maximum connected region algorithm,and the region edges are detected and filtered by the Canny operator.Thirdly,the navigation line in the current frame is extracted by fitting the region coordinate points.Then the dynamic weighted filtering algorithm is used to extract the navigation line for the soil and sky detection stage,respectively,and the navigation line for the sky detection stage is mirrored to the soil region.Finally,the Kalman filter algorithm is used to fuse and extract the final navigation path.The test results on 200 images show that the accuracy of visual navigation path fitting is 95.5%,and single frame image processing costs 60 ms,which meets the real-time and robustness requirements of navigation.The visual navigation experiments in Camellia oleifera orchard show that when the driving speed is 0.6 m/s,the maximum tracking offset of visual navigation in weed-free and weedy environments is 0.14 m and 0.24 m,respectively,and the RMSE is 30 mm and 55 mm,respectively.展开更多
文摘遮蔽检测是真正射影像生成的关键技术。提出一种基于多边形反演成像(polygon based inversion imaging,PBI)的遮蔽检测方法。利用建筑物表面多边形内部互不遮蔽的特点,以多边形为单元将建筑物逆投影到像方,反演成像时的目标状态,获得目标之间、多边形之间的遮蔽关系。为确保算法的稳健性和保真度,提出:①可疑区域增长法,稳健地栅格化复杂3维建筑物模型;②综合滤波模型用于消除多边形边界噪声。最后利用实例比较z-buffer方法,基于射线角度方法和PBI方法的遮蔽检测效果。结果表明,PBI算法的有效性和稳健性较好。
基金supported by the Doctoral Scientific Fund of the Ministry of Education of the People’s Republic of China(20120145120011)
文摘Visible light communications(VLC) have recently attracted a growing interest and can be a potential solution to realize indoor positioning,however,the performance of existing indoor positioning system is limited by multipath distortion inside a room.In order to combat the effect of multipath distortion,this paper proposes an LED-based indoor positioning algorithm combined with hybrid OFDM(HOFDM),in which asymmetrically clipped optical OFDM(ACOOFDM) is transmitted on the odd subcarriers while using pulse amplitude modulated discrete multitone(PAM-DMT) to modulate the imaginary part of each even subcarrier.In this scheme,we take a combined approach where a received-signal-strength(RSS) technique is employed to determine the location of the receiver and realize the 3-D positioning by Trust-region-based positioning.Moreover,a particle filter is used to further improve the positioning accuracy.Results confirm that this proposed positioning algorithm can achieve high accuracy even with multipath distortion,and the algorithm has better performance when combined with particle filter.
文摘Hand gestures are powerful means of communication among humans and sign language is the most natural and expressive way of communication for dump and deaf people. In this work, real-time hand gesture system is proposed. Experimental setup of the system uses fixed position low-cost web camera with 10 mega pixel resolution mounted on the top of monitor of computer which captures snapshot using Red Green Blue [RGB] color space from fixed distance. This work is divided into four stages such as image preprocessing, region extraction, feature extraction, feature matching. First stage converts captured RGB image into binary image using gray threshold method with noise removed using median filter [medfilt2] and Guassian filter, followed by morphological operations. Second stage extracts hand region using blob and crop is applied for getting region of interest and then “Sobel” edge detection is applied on extracted region. Third stage produces feature vector as centroid and area of edge, which will be compared with feature vectors of a training dataset of gestures using Euclidian distance in the fourth stage. Least Euclidian distance gives recognition of perfect matching gesture for display of ASL alphabet, meaningful words using file handling. This paper includes experiments for 26 static hand gestures related to A-Z alphabets. Training dataset consists of 100 samples of each ASL symbol in different lightning conditions, different sizes and shapes of hand. This gesture recognition system can reliably recognize single-hand gestures in real time and can achieve a 90.19% recognition rate in complex background with a “minimum-possible constraints” approach.
基金National Key Research and Development Program of China(2022YFD2202103)National Natural Science Foundation of China(31971798)+2 种基金Zhejiang Provincial Key Research&Development Plan(2023C02049、2023C02053)SNJF Science and Technology Collaborative Program of Zhejiang Province(2022SNJF017)Hangzhou Agricultural and Social Development Research Project(202203A03)。
文摘The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve autonomous navigation in orchard,a visual navigation method based on multiple images at different shooting angles is proposed in this paper.A dynamic image capturing device is designed for camera installation and multiple images can be shot at different angles.Firstly,the obtained orchard images are classified into sky and soil detection stage.Each image is transformed to HSV space and initially segmented into sky,canopy and soil regions by median filtering and morphological processing.Secondly,the sky and soil regions are extracted by the maximum connected region algorithm,and the region edges are detected and filtered by the Canny operator.Thirdly,the navigation line in the current frame is extracted by fitting the region coordinate points.Then the dynamic weighted filtering algorithm is used to extract the navigation line for the soil and sky detection stage,respectively,and the navigation line for the sky detection stage is mirrored to the soil region.Finally,the Kalman filter algorithm is used to fuse and extract the final navigation path.The test results on 200 images show that the accuracy of visual navigation path fitting is 95.5%,and single frame image processing costs 60 ms,which meets the real-time and robustness requirements of navigation.The visual navigation experiments in Camellia oleifera orchard show that when the driving speed is 0.6 m/s,the maximum tracking offset of visual navigation in weed-free and weedy environments is 0.14 m and 0.24 m,respectively,and the RMSE is 30 mm and 55 mm,respectively.
