The structure of 3 D range sensor system for unmanned vehicle is introduced.Several key technologies are described in detail.The ultrasonic signal is processed from different angles.Image edges are extracted by the m...The structure of 3 D range sensor system for unmanned vehicle is introduced.Several key technologies are described in detail.The ultrasonic signal is processed from different angles.Image edges are extracted by the multiple scale method.Image noises are recognized and cleared by using multilayer forward neural network with fuzzy logic.The method of information fusion for multiple sensors is discussed.This paper also gives some ultrasonic signal curves and image results.展开更多
A stereo matching algorithm based on the epipolar line constraint is designed to meet the real-time and the accuracy requirements. The algorithm is applied to photodynamic therapy binocular surveillance system for por...A stereo matching algorithm based on the epipolar line constraint is designed to meet the real-time and the accuracy requirements. The algorithm is applied to photodynamic therapy binocular surveillance system for port wine stain （PWS） when it monitors the position of the treatment region. The corner matching based on Hu moments is used to calculate the fundamental matrix of the binocular vision system. Experimental results are in agreement with the theoretical calculation.展开更多
A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black backg...A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.展开更多
Traditional information hiding algorithms cannot maintain a good balance of capacity,invisibility and robustness.In this paper,a novel blind colour image information hiding algorithm based on grey prediction and grey ...Traditional information hiding algorithms cannot maintain a good balance of capacity,invisibility and robustness.In this paper,a novel blind colour image information hiding algorithm based on grey prediction and grey relational analysis in the Discrete Cosine Transform(DCT) domain is proposed.First,this algorithm compresses the secret image losslessly based on the improved grey prediction GM(1,1)(IGM) model.It then chooses the blocks of rich texture in the cover image as the embedding regions using Double-dimension Grey Relational Analysis(DGRA).Finally,it adaptively embeds the compressed secret bits stream into the DCT domain mid-frequency coefficients,which are decided by those blocks' Double-Dimension Grey Correlation Degree(DGCD) and Human Visual System(HVS).This method can ensure an adequate balance between invisibility,capacity and robustness.Experimental results show that the proposed algorithm is robust against JPEG compression(46.724 6 dB when the compression quality factor is 90%),Gaussian noise(45.531 3 dB when the parameter is(0,0.000 5)) etc.,and it is a blind information hiding algorithm that can be extracted without an original carrier.展开更多
Inspired by eagle’s visual system,an eagle-vision-based object detection method for unmanned aerial vehicle(UAV)formation in hazy weather is proposed in this paper.To restore the hazy image,the values of atmospheric ...Inspired by eagle’s visual system,an eagle-vision-based object detection method for unmanned aerial vehicle(UAV)formation in hazy weather is proposed in this paper.To restore the hazy image,the values of atmospheric light and transmission are estimated on the basis of the signal processing mechanism of ON and OFF channels in eagle’s retina.Local features of the dehazed image are calculated according to the color antagonism mechanism and contrast sensitivity function of eagle’s visual system.A center-surround operation is performed to simulate the response of reception field.The final saliency map is generated by the Random Forest algorithm.Experimental results verify that the proposed method is capable to detect UAVs in hazy image and has superior performance over traditional methods.展开更多
A novel cast shadow detection approach was proposed.A stereo vision system was used to capture images instead of traditional single camera.It was based on an assumption that cast shadows were on a special plane.The im...A novel cast shadow detection approach was proposed.A stereo vision system was used to capture images instead of traditional single camera.It was based on an assumption that cast shadows were on a special plane.The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera.The points on the plane shared the same position between original image and the transformed image.As a result,the cast shadows can be detected.In order to improve the efficiency of cast shadow detection and decrease computational complexity,the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained.Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations.展开更多
Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabil...Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution, orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image based variable rate sprayer.展开更多
This letter proposes a new kind of image quality philosophy—Modulate Quality based on Fixation Points (MQFP) based on Human Visual System (HVS) model. Dissimilar to the former HVS-based quality assessment, the new me...This letter proposes a new kind of image quality philosophy—Modulate Quality based on Fixation Points (MQFP) based on Human Visual System (HVS) model. Dissimilar to the former HVS-based quality assessment, the new measure emphasizes particularly on modeling the jumping phenomenon of human sight instead of modeling the visual perception of human. In other words, to model the HVS using fixation points and stay-frequency instead of Contrast Sensitive Function (CSF) etc. which models the visual perception of HVS. The experiment on various frequency-distortion images indicates that the new measure is correlated with the subjective judgment more than the former HVS-based measure and is a robust measure.展开更多
文摘The structure of 3 D range sensor system for unmanned vehicle is introduced.Several key technologies are described in detail.The ultrasonic signal is processed from different angles.Image edges are extracted by the multiple scale method.Image noises are recognized and cleared by using multilayer forward neural network with fuzzy logic.The method of information fusion for multiple sensors is discussed.This paper also gives some ultrasonic signal curves and image results.
基金Supported by the National High Technology Research and Development Program of China("863"Program)(2007AA04Z231)~~
文摘A stereo matching algorithm based on the epipolar line constraint is designed to meet the real-time and the accuracy requirements. The algorithm is applied to photodynamic therapy binocular surveillance system for port wine stain （PWS） when it monitors the position of the treatment region. The corner matching based on Hu moments is used to calculate the fundamental matrix of the binocular vision system. Experimental results are in agreement with the theoretical calculation.
基金Project supported by the National Natural Science Foundation ofChina (No. 60008001) and the Natural Science Foundation of Zhe-jiang Province (No. 300297), China
文摘A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.
基金sponsored by the National Natural Science Foundation of China under Grants No.61170065,No.61003039,No.61202355the Science and Technology Support Project of Jiangsu under Grant No.BE2012183+4 种基金the Natural Science Key Fund for Colleges and Universities in Jiangsu Province under Grant No.12KJA520002the Postdoctoral Fund under Grants No.1101011B,No.2012M511753the Fund for Nanjing University of Posts and Telecommunications under Grant No.NY212047Fund of Jiangsu Computer Information Processing Technology Key Laboratory under Grant No.KJS1022the Priority Academic Program Development of Jiangsu Higher Education Institutions under Grant No.yx002001
文摘Traditional information hiding algorithms cannot maintain a good balance of capacity,invisibility and robustness.In this paper,a novel blind colour image information hiding algorithm based on grey prediction and grey relational analysis in the Discrete Cosine Transform(DCT) domain is proposed.First,this algorithm compresses the secret image losslessly based on the improved grey prediction GM(1,1)(IGM) model.It then chooses the blocks of rich texture in the cover image as the embedding regions using Double-dimension Grey Relational Analysis(DGRA).Finally,it adaptively embeds the compressed secret bits stream into the DCT domain mid-frequency coefficients,which are decided by those blocks' Double-Dimension Grey Correlation Degree(DGCD) and Human Visual System(HVS).This method can ensure an adequate balance between invisibility,capacity and robustness.Experimental results show that the proposed algorithm is robust against JPEG compression(46.724 6 dB when the compression quality factor is 90%),Gaussian noise(45.531 3 dB when the parameter is(0,0.000 5)) etc.,and it is a blind information hiding algorithm that can be extracted without an original carrier.
基金the Science and Technology Innovation 2030-Key Projects(Nos.2018AAA0102303,2018AAA0102403)the Aeronautical Science Foundation of China(No.20175851033)the National Natural Science Foundation of China(Nos.U1913602,U19B2033,91648205,61803011).
文摘Inspired by eagle’s visual system,an eagle-vision-based object detection method for unmanned aerial vehicle(UAV)formation in hazy weather is proposed in this paper.To restore the hazy image,the values of atmospheric light and transmission are estimated on the basis of the signal processing mechanism of ON and OFF channels in eagle’s retina.Local features of the dehazed image are calculated according to the color antagonism mechanism and contrast sensitivity function of eagle’s visual system.A center-surround operation is performed to simulate the response of reception field.The final saliency map is generated by the Random Forest algorithm.Experimental results verify that the proposed method is capable to detect UAVs in hazy image and has superior performance over traditional methods.
基金Project(40971219)supported by the Natural Science Foundation of ChinaProjects(201121202020005,T201221207)supported by the Fundamental Research Fund for the Central Universities,China
文摘A novel cast shadow detection approach was proposed.A stereo vision system was used to capture images instead of traditional single camera.It was based on an assumption that cast shadows were on a special plane.The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera.The points on the plane shared the same position between original image and the transformed image.As a result,the cast shadows can be detected.In order to improve the efficiency of cast shadow detection and decrease computational complexity,the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained.Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations.
文摘Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution, orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image based variable rate sprayer.
基金Supported by the National Natural Science Foundation of China (No.60372068) and theGuangdong Province Science Foundation (No.011628).
文摘This letter proposes a new kind of image quality philosophy—Modulate Quality based on Fixation Points (MQFP) based on Human Visual System (HVS) model. Dissimilar to the former HVS-based quality assessment, the new measure emphasizes particularly on modeling the jumping phenomenon of human sight instead of modeling the visual perception of human. In other words, to model the HVS using fixation points and stay-frequency instead of Contrast Sensitive Function (CSF) etc. which models the visual perception of HVS. The experiment on various frequency-distortion images indicates that the new measure is correlated with the subjective judgment more than the former HVS-based measure and is a robust measure.
