Machine Vision Analysis of Characteristics and Image Information Base Construction for Hybrid Rice Seed

Incompletely closed glumes, germination on panicle and disease are three important factors causing poor seed quality of hybrid rice. To determine how many and which categories should be classified to meet the demand for seed in rice production, the effects of various degrees of incompletely closed glumes, germination on panicle and disease on germination percentage at the harvest and after storage for six months were studied by standard germination percentage test. Six categories of seeds with germ (germinated seeds), severe disease, incompletely closed glumes, spot disease, fine fissure and normal seeds were inspected and then treated separately. Images of the five hybrid rice seed (Jinyou 402, Shanyou 10, Zhongyou 27, Jiayou 99 and Ⅱ you 3207) were acquired with a self-developed machine vision system. Each image could be processed to get the feature values of seed region such as length, width, ratio of length to width, area, solidity and hue. Then all the images of normal seeds were calculated to draw the feature value ranges of each hybrid rice variety. Finally, an image information base that stores typical images and related feature values of each variety was established. This image information base can help us to identify the classification limit of characteristics, and provide the reference of the threshold selection. The management of large numbers of pictures and the addition of new varieties have been supported. The research laid a foundation for extracting image features of hybrid rice seed, which is a key approach to future quality inspection with machine vision.

k-NN Based Bypass Entropy and Mutual Information Estimation for Incremental Remote-Sensing Image Compressibility Evaluation

Incremental image compression techniques using priori information are of significance to deal with the explosively increasing remote-sensing image data. However, the potential benefi ts of priori information are still to be evaluated quantitatively for effi cient compression scheme designing. In this paper, we present a k-nearest neighbor(k-NN) based bypass image entropy estimation scheme, together with the corresponding mutual information estimation method. Firstly, we apply the k-NN entropy estimation theory to split image blocks, describing block-wise intra-frame spatial correlation while avoiding the curse of dimensionality. Secondly, we propose the corresponding mutual information estimator based on feature-based image calibration and straight-forward correlation enhancement. The estimator is designed to evaluate the compression performance gain of using priori information. Numerical results on natural and remote-sensing images show that the proposed scheme obtains an estimation accuracy gain by 10% compared with conventional image entropy estimators. Furthermore, experimental results demonstrate both the effectiveness of the proposed mutual information evaluation scheme, and the quantitative incremental compressibility by using the priori remote-sensing frames.

High-resolution Remote Sensing Image Semi-global Matching Method Considering Geometric Constraints of Connection Points and Image Texture Information

Dense matching of remote sensing images is a key step in the generation of accurate digital surface models.The semi-global matching algorithm comprehensively considers the advantages and disadvantages of local matching and global matching in terms of matching effect and computational efficiency,so it is widely used in close-range,aerial and satellite image matching.Based on the analysis of the original semi-global matching algorithm,this paper proposes a semi-global high-resolution remote sensing image that takes into account the geometric constraints of the connection points and the image texture information based on a large amount of high-resolution remote sensing image data and the characteristics of clear image texture.123123The method includes 4 parts:①Precise orientation.Aiming at the system error in the image orientation model,the system error of the rational function model is compensated by the geometric constraint relationship of the connecting points between the images,and the sub-pixel positioning accuracy is obtained;②Epipolar image generation.After the original image is divided into blocks,the epipolar image is generated based on the projection trajectory method;③Image dense matching.In order to reduce the size of the cost space and calculation time,the image is pyramided and then semi-globally matched layer by layer.In the matching process,the disparity map expansion and erosion algorithm that takes into account the image texture information is introduced to restrict the disparity search range and better retain the edge characteristics of the ground objects;④Generate DSM.In order to test the matching effect,the weighted median filter algorithm is used to filter the disparity map,and the DSM is obtained based on the principle of forward intersection.Finally,the paper uses the matching results of WordView3 and Ziyuan No.3 stereo image to verify the effectiveness of this method.

System Supporting Automatic Generation of Finite Element Using Image Information

A mesh generating system has been developed in orde r to prepare large amounts of input data which are needed for easy implementation of a finite element analysis. This system consists of a Pre-Mesh Generator, an Automatic Mesh Generator and a Mesh Modifier. Pre-Mesh Generator produces the shape and sub-block information as input data of Automatic Mesh Generator by c arrying out various image processing with respect to the image information of th e drawing input using scanner. Automatic Mesh Generator generates mesh of trian gular elements in the arbitrarily shaped and multiple connected planar domain by using minimum necessary information. This generator has 3 methods of mesh gene ration for each sub-block, A) Regular Mesh Generation, B) Semi-Regular Mesh Ge neration and C) Irregular Mesh Generation. Any of them can be selected automati cally according to the external form of sub-block or the state of domain. Mesh Modifier projects and modifies the pattern of generated mesh by Automatic Mesh Generator as required. This system simplifies the user’s task while saving manp ower in carrying out the finite element analysis.

Over exposed image information recovery via stochastic resonance

Over exposure is rather annoying in photo taking. However, in some severe light conditions over exposure is inevitable using conventional cameras due to the limitation of dynamic range of the image sensor. The over exposed information would be completely lost and unrecoverable. In order to cope with this problem, we propose a novel technique in which the noise is used to enlarge the dynamic range of the image sensor. The essential mechanism that noise contributes to the information recovery is investigated. It is also proved that the visibility of regained information can reach the peak when specifically added noise is synchronized with the image sensor, thus activating the phenomenon of stochastic resonance （SR）. Four different types of noises are investigated to show the effects of variant distributions on the quality of recovered information. The experimental outcomes are consistent with our theoretical results, which indicates that the SR-based lost information recovery is quite promising.

The Image Property in an EIT Information Transfer System

We focus on the study of the transferred image property in an electromagnetically induced transparency （EIT）system. In our experiment, a triple-peak image is effectively transferred trom a coupling beam to a signal beam based on the FIT effect. It is found that the transferred image intensity profile of the signal beam is the same as that of the coupling beam while not in phase. Furthermore, the propagation property of the transferred image is studied. Due to the narrowing effect, the transferred image keeps narrowing and maintains the shape well within a certain distance outside of the medium. Our experimental results are in excellent agreement with the theoretical analysis.

ADAPTIVE RECONSTRUCTION TECHNIQUE FOR THE LOST INFORMATION OF THE RECTANGULAR IMAGE AREA

The adaptive reconstruction for the lost information of the rectangular image area is very important for the robust transmission and restoration of the image. In this paper, a new reconstruction method based on the Discrete Cosine Transform (DCT) domain has been put forward. According to the low pass character of the human visual system and the energy distribution of the DCT coefficients on the rectangular boundary, the DCT coefficients of the rectangular image area are adaptively selected and recovered. After the Inverse Discrete Cosine Transform (IDCT), the lost information of the rectangular image area can be reconstructed. The experiments have demonstrated that the subjective and objective qualities of the reconstructed images are enhanced greatly than before.

High-resolution Remote Sensing Image Semi-global Matching Method Considering Geometric Constraints of Connection Points and Image Texture Information

Dense matching of remote sensing images is a key step in the generation of accurate digital surface models.The semi-global matching algorithm comprehensively considers the advantages and disadvantages of local matching and global matching in terms of matching effect and computational efficiency,so it is widely used in close-range,aerial and satellite image matching.Based on the analysis of the original semi-global matching algorithm,this paper proposes a semi-global high-resolution remote sensing image that takes into account the geometric constraints of the connection points and the image texture information based on the large amount of high-resolution remote sensing image data and the characteristics of clear image texture.The method includes 4 parts:(1)Precise orientation.Aiming at the system error in the image orientation model,the system error of the rational function model is compensated by the geometric constraint relationship of the connecting points between the images,and the sub-pixel positioning accuracy is obtained;(2)Epipolar image generation.After the original image is divided into blocks,the epipolar image is generated based on the projection trajectory method;(3)Image dense matching.In order to reduce the size of the cost space and calculation time,the image is pyramided and then semi-globally matched layer by layer.In the matching process,the disparity map expansion and erosion algorithm that takes into account the image texture information is introduced to restrict the disparity search range and better retain the edge characteristics of the ground objects;(4)Generate DSM.In order to test the matching effect,the weighted median filter algorithm is used to filter the disparity map,and the DSM is obtained based on the principle of forward intersection.Finally,the paper uses the matching results of WordView3 and Ziyuan No.3 stereo image to verify the effectiveness of this method.

THE CLIMATIC STUDY OF CHANGBAI MOUNTAIN BY INTEGRATION OF REMOTE SENSING INFORMATION AND GEO-CODED IMAGES

Ⅰ. INTRODUCTION Changbai Mountain is situated between E127°54′-128°08′, N40°58′-42°06′ about 2700 meters above sea level. It is the typical area of the mountainous climate in the monsoon area of the temperate zone on the globe. The well reserved primeval vertical distribution of natural landscape belts and the Natural Conservation of Changbai Mountains adopted by the UNESCO′s MAB Program cause the worldwide attention of geographers. Beside the complexity of the climatic structure itself, the mechanical effection of the high mountain body also effect the climate in the eastern part of China. In the mountain area where short of meteorological observation data, the climatic study by remote sensing is favorable for discovery and representation of climatic law in large area.

Fast Texture Segmentation Based on Semi-Local Region Descriptor and Active Contour

In this paper, we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model. We address the problem of textures where neither the gray-level information nor the boundary information is adequate for object extraction. This is often the case of natural images composed of both homogeneous and textured regions. Because these images cannot be in general directly processed by the gray-level information, we propose a new texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry. Then, we use the popular Kullback-Leibler distance to design an active contour model which distinguishes the background and textures of interest. The existence of a minimizing solution to the proposed segmentation model is proven. Finally, a texture segmentation algorithm based on the Split-Bregrnan method is introduced to extract meaningful objects in a fast way. Promising synthetic and real-world results for gray-scale and color images are presented.

Image Hiding Algorithm in Discrete Cosine Transform Domain Based on Grey Prediction and Grey Relational Analysis

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.

Negative exponential behavior of image mutual information for pseudo-thermal light ghost imaging： observation, modeling, and verification

When using the image mutual information to assess the quality of reconstructed image in pseudothermal light ghost imaging, a negative exponential behavior with respect to the measurement number is observed. Based on information theory and a few simple and verifiable assumptions, semi-quantitative model of image mutual information under varying measurement numbers is established. It is the Gaussian characteristics of the bucket detector output probability distribution that leads to this negative exponential behavior. Designed experiments verify the model.

The Rehabilitated Image in the Written Press in Cameroon and Its Mediation Challenges: The Example of <i>Cameroon Tribune</i>

The Cameroonian daily press is now taking a new look at the use of photography in its columns. Photography is therefore at the heart of the new information system: the application of a new formula, a photographic formula, therefore visual, which is a novelty. The aim of our article is to highlight how the Cameroonian daily press constructs the discursive staging of this visual content. It proposes to examine the ways in which the news image in Cameroon Tribune is constituted in journalistic writing. In this article, we will analyse the photographic content of the daily newspaper Cameroon Tribune. The corpus consists of 1245 photographs from 25 issues published between 21 October and 22 November 2019. The technique used is media content analysis, which allows us to produce exhaustive descriptive statements that meet the criteria of scientific validity and reproducibility. Emancipated from its strict illustrative function, photography in the daily newspaper Cameroon Tribune then becomes fully a means of information and communication, in the same way as text. This translates into the construction of informative sets such as the importance of the surface area of the visual content which gives pride of place to the visual, giving an impression of abundance that is perceptible from the Front Page. One of the important features of the newspaper’s iconography is the great positivity of its images, which reinforces the closeness between the reader and the news. In total, the newspaper highlights photographs of limited informative interest: these are portraits that show the faces of the protagonists of the articles, to the detriment of current events.

Novel Model Using Kernel Function and Local Intensity Information for Noise Image Segmentation

It remains a challenging task to segment images that are distorted by noise and intensity inhomogeneity.To overcome these problems, in this paper, we present a novel region-based active contour model based on local intensity information and a kernel metric. By introducing intensity information about the local region, the proposed model can accurately segment images with intensity inhomogeneity. To enhance the model＇s robustness to noise and outliers, we introduce a kernel metric as its objective functional. To more accurately detect boundaries, we apply convex optimization to this new model, which uses a weighted total-variation norm given by an edge indicator function. Lastly, we use the split Bregman iteration method to obtain the numerical solution. We conducted an extensive series of experiments on both synthetic and real images to evaluate our proposed method, and the results demonstrate significant improvements in terms of efficiency and accuracy, compared with the performance of currently popular methods.

Modeling of information images dynamics through the communicative field method

This work presents a formalized description of information and communicative interac- tions of individuals on the basis of the communicative field （CF） method. It also contains explication of the possibility to create model of information and communication inter- actions, which is able to illustrate both interactions between two and more individuals. Methods and approaches which are suggested in this paper can correctly simulate the processes of distortion and generation of information images （IIs） with information and communication social interaction. Expansion and addition of IIs theory in terms of the transmission of information between individuals allows us to speak about the space of IIs. This space helps to explain a number of characteristic phenomena of human thinking.

Modeling of cognitive brain activity through the information images theory in terms of the bilingual Stroop test

The paper presents the basic principles of the information image theory and a mathematical model developed using it. The hierarchy of information images in an individual mind, which determines his／her real and virtual activity, is considered. Algo- rithms for describing transfer and distortion of information images by individuals in the communication process are constructed. To corroborate the theory experimentally, the bilingual Stroop test is used. The results of the test are interpreted using the introduced theory, and are then compared with the results of computer modeling based on the theory. It is shown that information images can be used not only to explain a number of cognitive processes of the human mind, but also to predict their dynamics in a number of particular cases.

The theory of information images： Modeling based on diffusion equations

This work represents a formalized description of information and communicative interac- tions of individuals on the basis of theory of information images （II）. It also demonstrates how important it is to choose the models type adequate to the systems under research. It also introduces an explication of the possibility to create the model of information and communication interactions that can illustrate transmission of information between two and more individuals. Methods and approaches suggested in this paper allow us to compare different levels of the described processes depending on the chosen architecture of the model; the methods and approaches mentioned in the current work can be also used to simulate the processes of distortion and generation of information images while information and communication social interaction. Expansion and addition of informa- tion images theory in terms of transmission of information among individuals enables us to speak about the space of individual II. The existence of such a space and creation of correct formalized model help us to explain a number of characteristic phenomena of human thinking processes. As a result of this research, the authors introduce an equa- tion that describes the spatial and structural evolution of individual II. There is also an example of modeling on the basis of this theory taking into account the results of the experiment （bilingual Stroop test）.