写实与意象:新时代中国画“视觉图像”的构建

新时代中国画由于受到西方绘画的影响和新旧艺术思潮的碰撞,已然变得不再那样纯粹。“视觉图像”信息的不断冲击也造成了中国画“写意”精神的缺失。因此,研究新时代中国画的理论框架与精神指向要着眼传统,并结合现代视角,从中西方文化体系的差异中判断时下中国画的审美观,探寻“视觉文化”背景下新时代中国画的变革方向,确立中国画在当代美术史中的地位。

东周君主陵墓对“地下宫殿”的视觉表现

通过"视觉"图像为国君的灵魂在地下世界安宅立家,以使其长久永生。这一传统在东周时期已经比较成熟。无论是春秋时期楚国大臣鬻拳葬楚文王于地宫等文献信息,还是湖北随县的战国初期曾侯乙墓,抑或是陕西凤翔出土的春秋晚期秦雍都一号陵园1号大墓,其所呈现的为死者营造"地下宫殿"的主题都是较为明显的。此种图像表现也直接对秦汉时代帝王陵墓的营造产生了一定影响。

Feature-based sequential partial vision measurement method for large scale machine parts

To realize the high-precision vision measurement for large scale machine parts, a new vision measurement method based on dimension features of sequential partial images is proposed. Instead of mosaicking the partial images, extracting the dimension features of the sequential partial images and deriving the part size according to the relationships between the sequential images is a novel method to realize the high- precision and fast measurement of machine parts. To overcome the corresponding problems arising from the relative rotation between two sequential partial images, a rectifying method based on texture features is put forward to effectively improve the processing speed. Finally, a case study is provided to demonstrate the analysis procedure and the effectiveness of the proposed method. The experiments show that the relative error is less than 0. 012% using the sequential image measurement method to gauge large scale straight-edge parts. The measurement precision meets the needs of precise measurement for sheet metal parts.

3-D visual tracking based on CMAC neural network and Kalman filter

In this paper, the Kalman filter is used to predict image feature positionaround which an image-processing window is then established to diminish feature-searching area andto heighten the image-processing speed. According to the fundamentals of image-based visual servoing(IBVS), the cerebellar model articulation controller (CMAC) neural network is inserted into thevisual servo control loop to implement the nonlinear mapping from the error signal in the imagespace to the control signal in the input space instead of the iterative adjustment and complicatedinverse solution of the image Jacobian. Simulation results show that the feature point can bepredicted efficiently using the Kalman filter and on-line supervised learning can be realized usingCMAC neural network; end-effector can track the target object very well.

Research on detection of lane based on machine vision

To prevent a vehicle from departing the lane in assistant or automatic steering, real-time vision-based detection of lane is studied. The system architecture, detecting principle and lane model are described. Then the detecting algorithm of the lane image is discussed in detail. In this algorithm, several proper sub-windows in one image are first selected as the processing regions. To every sub-window, by means of such steps as appropriate pre-processing, edge detection and Hough transform, etc., the lane description features are extracted. Experimental results reveal that this detection method is of good real-time, high recognition reliability and strong robustness, etc., which can provide the decision-making foundation for the following automatic or assistant steering to some extent.

NEW CORNER DETECTION ALGORITHM BASED ON MULTI-FEATURE SYNTHESIS

Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditional corner properties. Based on the two properties, the concept of the fuzzy set is introduced into a detection. Secondly, the extracted-formulae of three groups including the features of the corner subject degree are derived. Through synthesizing the features of three groups, the judgments of the corner detection, location, and optimization are obtained. Finally, by using the algorithm the detection results of several examples and feature curves for some interested parts, as well as the detection results for the test images history in references are given. Results show that the algorithm is easily realized after adopting the fuzzy set, and the detection effect is very ideal.

Application of Computer Vision Technique to Maize Variety Identification

Variety identification is important for maize breeding, processing and trade. The computer vision technique has been widely applied to maize variety identification. In this paper, computer vision technique has been summarized from the following technical aspects including image acquisition, image processing, characteristic parameter extraction, pattern recognition and programming softwares. In addition, the existing problems during the application of this technique to maize variety identification have also been analyzed and its development tendency is forecasted.

RIGHT INFERIOR FRONTAL GYRUS PROCESSING OF VISUAL EROTIC INFORMATION BASED ON fMRI

Visually-induced erotic arousal evoked by pornographic visual stimuli, such as films or photographs, is a common occurrence in human behavior. The brain activation associated with visual erotic stimuli in heterosexual right handed females is studied. Functional magnetic resonance imaging is used to investigate 15 female partici- panterotic arousal induced by visual stimuli in film and picture forms, respectively, performing three or more times during their menstrual cycle on a 3.0T magnetic resonance imaging scanner. There is activation of a set of bilateral brain areas, including the inferior lateral occipital cortex, the anterior supramarginal gyrus, the parietal operculum cortex, the superior parietal lobules, the right inferior frontal gyrus, the cerebellum, the hypothalamus, the thalamus, the hippocampus, and the mid-brain. From different regions, the brain activation is observed and the inferior frontal gyrus has found to be task-independent. Furthermore, the right inferior frontal gyrus has more activation than the left inferior frontal gyrus. The result shows that the right inferior frontal gyrus plays an important role in pornographic information processing rather than being activated stimuli property specific. It is presented for the first time that the functional laterization of the inferior frontal gyrus is bi-directional rather than single （left） directional.

A method for workpiece surface small-defect detection based on CutMix and YOLOv3

Surface small defects are often missed and incorrectly detected due to their small quantity and unapparent visual features.A method named CSYOLOv3,which is based on CutMix and YOLOv3,is proposed to solve such a problem.First,a four-image CutMix method is used to increase the small-defect quantity,and the process is dynamically adjusted based on the beta distribution.Then,the classic YOLOv3 is improved to detect small defects accurately.The shallow and large feature maps are split,and several of them are merged with the feature maps of the predicted branch to preserve the shallow features.The loss function of YOLOv3 is optimized and weighted to improve the attention to small defects.Finally,this method is used to detect 512×512 pixel images under RTX 2060Ti GPU,which can reach the speed of 14.09 frame/s,and the mAP is 71.80%,which is 5%-10%higher than that of other methods.For small defects below 64×64 pixels,the mAP of the method reaches 64.15%,which is 14%higher than that of YOLOv3-GIoU.The surface defects of the workpiece can be effectively detected by the proposed method,and the performance in detecting small defects is significantly improved.

2D IMAGE BASED SIEVING FOR PARTICLE AGGREGATE GRADATION

Acquiring the size gradation for particle aggregates is a common practice in the granule related industry,and mechanical sieving or screening has been the normal method. Among many drawbacks of this conventional means,the major ones are time-consuming,labor-intensive,and being unable to provide real-time feedback for process control. In this letter,an optical sieving approach is introduced. The two-dimensional images are used to develop methods for inferring particle volume and sieving behavior for gradation purposes. And a combination of deterministic and probabilistic methods is described to predict the sieving behaviors of the particles and to construct the gradation curves for the aggregate sample. Comparison of the optical sieving with standard mechanical sieving shows good correlation.

Application of Computer Vision Technology in Agriculture

With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-research progress on diagnosis of agricultural products, water diagnosis, weed identification,product quality testing and grading, agricultural picking and sorting and other as- pects, and finally put forward its existing problems and prospects for the future.

Cast shadow detection for moving objects based on binocular stereo vision

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.

Measuring Propeller Blade Width Using Binocular Stereo Vision

Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.

A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

MULTI-WATERMARKING SCHEME FOR GROUP USERS BASED ON VISUAL CRYPTOGRAPHY

All watermarks are shared into shadow images using VCS(Visual Cryptography Scheme). Only one specific shadow (as a new watermark) is embedded into the host signal and the other ones are distributed to every user in each group as a key. In the watermarking extraction procedure, users in different group can obtain different watermark by combining their shadows with the extracted one from the watermarked signal. Analysis and experimental results show that the new watermarking method is novel, secure and robust.

Eagle-Vision-Based Object Detection Method for UAV Formation in Hazy Weather

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.

Study of Image Denoising in Robot Visual Navigation System

In the technique of robot-assisted invasive surgery, high quality image is a key factor of the visual navigation system. In this paper, the authors have made a study of the image processing in visual system. Based on the analysis of plentiful demising methods, they proposed a new method （S-AM-W） which oxnbines Adaptive Median filter and Wioaer filter to renmve the main noises （Salt ＆ Pepper noise and Gattssian noise）. The sinlflation results show that it is simple, well real time, and has high Peak Signal-to-Noise Ratio （PSNR）. It was found that the new method is effective and efficient in dealing with medical image of background noise.

Realtime Vision-Based Surface Defect Inspection of Steel Balls

In the proposed system for online inspection of steel balls, a diffuse illumination is developed to enhance defect appearances and produce high quality images. To fully view the entire sphere, a novel unfolding method is put forward based on geometrical analysis, which only requires one-dimensional movement of the balls and a pair of cameras to capture images from different directions. Moreover, a realtime inspection algorithm is customized to improve both accuracy and efficiency. The precision and recall of the sample set were 87.7% and 98%, respectively. The average time cost on image processing and analysis for a steel ball was 47 ms, and the total time cost was less than 200 ms plus the cost of image acquisition and balls' movement. The system can sort 18 000 balls per hour with a spatial resolution higher than 0.01 mm.

Detecting and Tracking Moving Targets on Omnidirectional Vision

A method was presented to implement the detecting and tracking of moving targets through omnidirec-tional vision. The method combined optical flow with particle filter arithmetic, in which optical flow field was used to detect and locate moving targets and particle filter was used to track the detected moving objects. According to the circular image character of omnidirectional vision, the calculation equation of optical flow field and the tracking arithmetic of particle filter were improved based on the polar coordinates at the omnidirectional center. The edge of a randomly moving object could be detected by optical flow field and was surrounded by a reference region in the particle filter. A dynamic motion model was established to predict particle state. Histograms were used as the fea-tures in the reference region and candidate regions. The mutual information (MI) and Gaussian function were com-bined to calculate particle weights. Finally, the state of tracked object was computed by the total particle states with weights. Experiment results show that the proposed method could detect and track moving objects with better real-time performance and accuracy.

A Machine Vision System for Ball Grid Array Package Inspection

An optical inspection method of the Ball Grid Array package(BGA) was proposed by using a machine vision system. The developed machine vision system could get main critical factors for BGA quality evaluation, such as the height of solder ball, diameter, pitch and coplanarity. The experiment has proved that this system is available for BGA failure detection.