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Combining the intelligent algorithm such as BP neural network and support vector maching (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment. Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional...
A neural network model with adaptive structure for image annotation is proposed in this paper. The adaptive structure enables the proposed model to utilize both global and regional visual features, as well as correlative information of annotated keywords for annotation. In order to achieve an approximate global optimum rather than a local optimum, both genetic algorithm and traditional back-propagation...
The objective of this research is to develop algorithm to recognize unsound wheat based on image processing and artificial neural network. The sample used for this study involved wheat from major producing areas of China. Images of wheat were acquired with a color machine vision system. Each image was processed to extract shape and color quantitative features. All features were analyzed with principal...
A method for the traffic signal recognition of his color space and bp neural network algorithm. First convert the traffic signal images from RGB space to HSI space, and then extracted H Component characteristics from HSI space in the traffic signal images, according to the Component histogram, determine the signal color. Finally, BP neural network is applied for the traffic signal lights recognition...
Since the current fashion color forecasts have some disadvantages in practical application, there is considerable interest in building models that can predict fashion value of the colors precisely and swiftly from historical data. This paper proposed a new forecasting model called G-LMBPNN (Gray Levenberg-Marquardt Back Propagation Neural Network). It utilizes gray process to obscure the data sequence...
In this paper, we adopt BP neural network as classification method and established the emotion model to simulate people's emotion based on image template. For achieving this purpose, firstly, we used 9 images which has different features of the famous psychologist Furnham's Shape & Color Test as templates and the basis of emotion classification. Then, we got a vector which has 27 dimensions by...
Obtaining color constancy is the study focuses in the field of image vision which does not alter with light source illumination modification. In consideration of the influence of the light source fluctuations on the image color, this paper puts forward an image color constancy algorithm based on BP neural network. This algorithm was used for testing different light source and illumination intensity...
An adaptive learning rate Backpropagation Neural Network (BPNN) is proposed to image segmentation of rice disease spots. Rice blast is a common disease of rice and is tested in this paper. Firstly, the combination of different color feature parameters is selected as the input of the BPNN. Secondly, a BPNN with 5 input, 10 hidden neurons and 1 output is constructed to rice blast spots segmentation...
Rice leaf diseases have occurred all over the world, including china. They have had a significant impact on rice quality and yield. Now, the control method rely mainly on artificial means.In this study, BP neural network classifiers were designed for classifying the healthy and diseased parts of rice leaves. This paper select rice brown spot as study object, the training and testing samples of the...
At present, the textile image is separated by manpower with low efficiency. In order to deal with this problem, this paper proposes a novel algorithm for textile image separation based on back propagation artificial neural network. The factors that can affect the result of image separation are the RGB values of a pixel itself, the color of its adjacent pixels, and its boundary probability. According...
According to the retrieval algorithm of adjusting automatic the weight of multi-features, and which the algorithm exist some deficiency, like that have not the study mechanism and so on. The paper analyzed and studied in the BP neural network in the learning process, and has realized the image retrieval method based on the BP neural network relevance feedback technology. The experiment proved that...
Human brain can detect faces from the images constructed in their eyes. The face detection is a computerize method of locating the face in the digital image. It is an important challenge to locate faces from uncontrolled and indistinguishable background of the digital image. This paper presents human face detection from the colored images. Skin color segmentation is used for localizations of skin...
Two main questions are researched in this paper, which are how to establish the ICC profile, and how to precisely describe and record the device's color rendering characteristic. The process of establishing ICC profile of color printer and data standardization are expounded in detail. An improved BP neural network is used to convert color data between the native device color space and the PCS. Meanwhile,...
The new automatic classification devices for products based on machine vision techniques value the shape and color parameters so as to suitably assess the latter. These parameters may also be turned to good account by the machine vision techniques that proved to be applicable in several domains. One can especially apply these techniques in the inspection and analysis systems of industrial products...
According to the chromaticity theory, the computer vision system used in color quantitative measurement was developed, which was marked by the 1980A color luminance meter. Munsell color system is selected to establish the mutual conversion between RGB and L*a*b* color model for camera, the conversion relation between RGB color space of CCD camera and L*a*b* color space under a big color gamut was...
In this paper, we propose a real-time forest fire detection algorithm using artificial neural networks based on dynamic characteristics of fire regions segmented from video images. Fire region is obtained from image with the help of threshold values in HSV color space. Area, roundness and contour are computed for fire regions from each 5 continuous frames. The average and mean square deviation of...
A new approach for image classification based on the color information, shape and texture is presented. In this work, we use the three RGB bands of a color image in RGB model to extract the describing features. All the images in image database are divided into 6 parts. We use the Daubechies 4 wavelet transform and first order color moments to obtain the necessary information from each part of the...
In order to insure safety of driving vehicle in the driver assistance system and effective navigation in the automatic driving system, a new recognition method based on the neural network and the invariant moments for traffic signs was proposed in this paper. Firstly, the area of the traffic sign was located from the complicated image background. Secondly, the features of each traffic sign were obtained...
This paper proposes an algorithm of BP neural network, which reproduces a color image under D65 light conditions by using a pair of images (one with no D65 light source, and the other with D65 light source). The result of reproduction image which used a fluorescent lamp as an unknown light source is presented. This algorithm successfully removes the effect of the unknown light source color and achieves...
To improve the performance of appearance-based three-dimensional object recognition system, we propose to extract Hupsilas moment invariants, affine moment invariants and color moments from the 2D images of 3D objects. Hupsilas and affine moment invariants have the properties of rotation, scale, translation invariance and affine transformation invariance respectively for the objects in images, and...
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