Image information compression in the image recognition process: medical example

1995 ◽  
Author(s):  
Jacek Galas
Keyword(s):  
Image Recognition ◽  
Information Compression ◽  
Image Information ◽  
Recognition Process

scholarly journals Research on the Application of Artificial Intelligence Machine Learning Technology in Improving the Accuracy of Engineering Image Processing

2021 ◽  
Vol 2083 (4) ◽  
pp. 042007
Author(s):  
Xiaowen Liu ◽  
Juncheng Lei
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Deep Learning ◽  
Image Recognition ◽  
Recognition Performance ◽  
Color Space ◽  
Gaussian Model ◽  
Image Feature ◽  
Layer By Layer ◽  
Image Information

Abstract Image recognition technology mainly includes image feature extraction and classification recognition. Feature extraction is the key link, which determines whether the recognition performance is good or bad. Deep learning builds a model by building a hierarchical model structure like the human brain, extracting features layer by layer from the data. Applying deep learning to image recognition can further improve the accuracy of image recognition. Based on the idea of clustering, this article establishes a multi-mix Gaussian model for engineering image information in RGB color space through offline learning and expectation-maximization algorithms, to obtain a multi-mix cluster representation of engineering image information. Then use the sparse Gaussian machine learning model on the YCrCb color space to quickly learn the distribution of engineering images online, and design an engineering image recognizer based on multi-color space information.

scholarly journals Fuzzy Logic Using in Images Retrieval Depending on Their Features

2019 ◽  
Vol 54 (5) ◽  
Author(s):  
Faiez Musa Lahmood Alrufaye ◽  
Mohammed Muanis I. Al-Sagheer ◽  
Marwah Thamer Ali
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Fuzzy Logic ◽  
Computer Science ◽  
Image Recognition ◽  
Correct Result ◽  
Image Information ◽  
Fuzzy Logic Algorithm ◽  
Image Characteristics ◽  
Content Information

Image processing has become one of the most important branches of computer science, especially after entering into several areas of life such as medicine, engineering and various sciences. In our current research, we have developed a system of image recognition based on image characteristics and some content information using the most important artificial intelligence algorithms, a fuzzy logic algorithm, to obtain complete image information using small values ranging from 0 to 1. The program was executed on a set of standard database called the WANG database. It holds the contents of 1000 images from the Corel stock photo database, in JPEG format. The system was evaluated using the recall method. This method calculates the proportion of correct results identified by the system as correct results with correct result identified by the classic system.

Study on the Image Process of Wheels Based on Machine Vision

2011 ◽  
Vol 179-180 ◽  
pp. 914-919
Author(s):  
Shi Feng Wang ◽  
Chang Chun Li ◽  
Jing Yu ◽  
Tian Hou Zhang
Keyword(s):  
Feature Extraction ◽  
Machine Vision ◽  
Edge Detection ◽  
Image Recognition ◽  
Image Feature ◽  
Image Process ◽  
Image Feature Extraction ◽  
Image Information ◽  
Industrial Cameras

This paper introducted the machine vision technology into the field of wheel suspension coating, used the industrial cameras for the image information of the wheel center and the valve hole, did the edge detection of the valve hole and the wheel based on visual c++ platform ,making the image feature extraction and analysis, thus completing image recognition of the wheel center and the valve hole, realized hang the wheels to the conveyor of automatically.

scholarly journals EKSTRAKSI FITUR AKSARA BALI MENGGUNAKAN METODE ZONING

2015 ◽  
Vol 14 (2) ◽  
pp. 44
Author(s):  
I Wayan Agus Surya Darma ◽  
I K. G. Darma Putra ◽  
Made Sudarma
Keyword(s):  
Feature Extraction ◽  
Image Recognition ◽  
Character Recognition ◽  
Recognition System ◽  
Important Process ◽  
Recognition Process ◽  
Multiple Regions ◽  
Test Result

Feature extraction is an important process in character recognition system. The purpose of this process is to obtain special feature from a character image. This paper is focuses on how to obtain special feature from a handwritten Balinese character image using zoning. This algorithm dividing Balinese character image into multiple regions, then a special feature on each region resulting the data extracted feature. The test result in this paper generates a various  semantic and direction feature data. This is because this paper using handwritten Balinese character. Furthermore, the features that produced in this paper can be used on Balinese character image recognition process

Oil Leak Image Data Analysis Based on Maximum Variance Threshold Method

2014 ◽  
Vol 687-691 ◽  
pp. 3564-3568
Author(s):  
Xi Zhang ◽  
Lei Zhang ◽  
Yu Feng Zhang
Keyword(s):  
Data Analysis ◽  
Image Recognition ◽  
Computer Image ◽  
Image Data ◽  
Threshold Method ◽  
Threshold Segmentation ◽  
Image Information ◽  
Maximum Variance ◽  
Recognition Technique

The oil leak is detected by the computer image recognition technique and the oil leak images are processed by the threshold segmentation and semi-thresholding of the maximum variance threshold method. Through capture of fluorescent images of leakage, the oil leak image information is acquired. The maximum variance threshold method is adopted for image data analysis to compute the dilation area of oil images and achieve the detection of leakage.

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