scholarly journals Research on Image Pretreatment Technique in Recognition of Handwritten Number

2016 ◽  
Vol 06 (06) ◽  
pp. 329-332
Author(s):  
翠芳 张
Keyword(s):  
Image Pretreatment

Research on Color Vegetable Diseases in Greenhouse Image Pretreatment and Extraction Method

2014 ◽  
Vol 989-994 ◽  
pp. 3730-3733 ◽  
Author(s):  
Xiao Li Luo
Keyword(s):  
Average Method ◽  
Extraction Method ◽  
Moving Average ◽  
Accurate Identification ◽  
Sobel Operator ◽  
Computer Image Processing ◽  
Gradient Magnitude ◽  
Image Pretreatment ◽  
Intelligent Recognition ◽  
Channel Image

In order to realize the accurate identification of the image color vegetable diseases in Greenhouse, In this paper, by using computer image processing technology in the intelligent recognition of vegetable diseases in greenhouse leaf, First, the moving average method can effectively remove the noise by the image of R,G, B three channel gray level, Then separate three channel image using Sobel-operator and the 4 template based on the direction of gradient magnitude ,and then integrate the three channel edge ,it can overcome the shortcoming of traditional gray image information, and make up the deficiency of the traditional Sobel operator edge thinning geometric features.

Recognition of Vehicles on Geometric Morphology

2011 ◽  
Vol 217-218 ◽  
pp. 27-32
Author(s):  
Guo Feng Qin ◽  
Yu Sun ◽  
Qi Yan Li
Keyword(s):  
Computer Vision ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Traffic Management ◽  
Template Matching ◽  
Recognition System ◽  
Automatic Recognition ◽  
Vehicular Traffic ◽  
Image Pretreatment ◽  
Geometric Morphology

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. This article introduces an Automobile Automatic Recognition System based on image. It begins with the structures of the system. Then detailed methods for implementation are discussed. This system take use of a camera to get traffic images, then after image pretreatment and segmentation, do the works of feature extraction, template matching and pattern recognition, to identify different models and get vehicular traffic statistics. Finally, the implementation of the system is introduced. The algorithms of recognized process were verified in this application case.

High Resolution RS Image Industrial Solid Wastes Extraction Based on SVM

2014 ◽  
Vol 543-547 ◽  
pp. 2318-2322
Author(s):  
Xiu Hong Yao ◽  
Wen Xing Bao
Keyword(s):  
High Resolution ◽  
Anisotropic Diffusion ◽  
Feature Recognition ◽  
Solid Wastes ◽  
Shape Features ◽  
Operation Efficiency ◽  
Diffusion Filtering ◽  
Extraction Algorithm ◽  
Image Pretreatment ◽  
Fast Extraction

In order to accurately extract various types of industrial solid wastes from high resolution RS images, a industrial solid wastes feature fast extraction algorithm was proposed based on SVM. The reasonable image pretreatment was conducted by anisotropic diffusion filtering firstly. It is because that high resolution RS image contains abundant information and industrial solid wastes heap was very complex, we proposed the classification algorithm based on 1-v-1 which could extract multi-class industrial solid wastes fast and accurately at once. The new algorithm improved both efficiency and accuracy of industrial solid wastes recognition. The experimental results show that the industrial solid wastes feature recognition of SVM has better advantages than conventional methods. The new algorithm can recognize not only shape features of industrial solid wastes heap but also its material and type and it is constructed to recognize multi-class industrial solid wastes with higher operation efficiency.

scholarly journals KLASIFIKASI DAN IDENTIFIKASI JUMLAH KOLONI PADA CITRA BAKTERI DENGAN METODE K-NEAREST NEIGHBOR

MATICS ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 76
Author(s):  
Ihsan Ihsan
Keyword(s):  
Nearest Neighbor ◽  
Lactobacillus Bulgaricus ◽  
K Nearest Neighbor ◽  
Contrast Stretching ◽  
Image Pretreatment ◽  
F Measure ◽  
Photo Image

<p class="Abstract"><em>Abstract</em> – This study proposes a system for classification and counting the number of bacterial colonies using a photo image of bacteria. The system uses several image pretreatment process. Including Contrast Stretching, <em>Extended-Maxima Transform</em>, and <em>Regionprops</em>. The main purpose of this system is to determine the category of colonies of bacteria in large quantities can not be done manually. To build the algorithms necessary features must be determined such as <em>diameter, perimeter and roundness</em> method of determining the categories using KNN <em>(K-Nearest Neighbor)</em>. As a results of this research is classify three types of bacteria such as Lactobacillus Bulgaricus, Streptococcus thermophiles, and bifidobakterium Precision with a percentage of 97,97% and 87,09% F-Measure</p><p><strong>Keywords: Contrast Stretching, Lactobacillus, Regionprops, K-Nearest Neighbor</strong></p>

MMW Radiometric Image Feature Extraction for Security Inspection

2012 ◽  
Vol 236-237 ◽  
pp. 999-1003
Author(s):  
Qi Wang ◽  
Guang Feng Zhang
Keyword(s):  
Imaging System ◽  
Image Feature ◽  
Imaging Method ◽  
Canny Operator ◽  
Radiation Imaging ◽  
Security Inspection ◽  
Image Pretreatment ◽  
Morphology Algorithm ◽  
Morphology Filter

Millimeter-wave (MMW) radiometric imaging system is widely used in the field of military and civil affairs. It can be used to detect concealed objects hidden under clothing. Based on MMW radiation imaging method and morphology theory, we presented a complex morphology filter to do the image pretreatment. Then used the Canny operator to extract features from concealed objects. The results show that the morphology algorithm can improve the quality of radiometric images. Meanwhile, Canny algorithm can detect the edges of object well.

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