scholarly journals APLICAÇÃO DE REDES NEURAIS CONVOLUCIONAIS NO RECONHECIMENTO DE CARACTERES EM PLACAS INFORMATIVAS JAPONESAS

2021 ◽  
Vol 13 (2) ◽  
pp. 12-24
Author(s):  
Rafael Yuji Hirata Furusho ◽  
Francisco Assis da Silva ◽  
Leandro Luiz de Almeida ◽  
Danillo Roberto Pereira ◽  
Mário Augusto Pazoti ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Edge Detection ◽  
Convolutional Neural Network ◽  
Mathematical Morphology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Processing Techniques ◽  
Processing Techniques

Unlike most Western countries, which have a Latin-derived base alphabet, Japan has two syllabic alphabets called Hiragana and Katakana, and a Chinese alphabet, called Kanji. The vast differences in the writing of these Eastern alphabets to Western alphabets, Western alphabet-based OCR algorithms tend not to efficiently detect Japanese characters. This work contributes to a methodology applying digital image processing techniques, such as color range-based segmentation, edge detection and mathematical morphology techniques, to detect Japanese traffic informationalplates correctly the perspective and segment the characters contained in it. A convolutional neural network wasused to perform the classification of Hiragana characters contained in the segmented plates, withaccuracyof 94.37%.

scholarly journals Identification and Classification of Lung Nodules Using Neural Networks

2021 ◽  
Vol 12 (6) ◽  
pp. 1956-1961
Author(s):  
Dr. S. Gnanavel Et al.
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Feature Extraction ◽  
Digital Image Processing ◽  
Digital Image ◽  
Extraction Process ◽  
Health Concern ◽  
Image Processing Techniques ◽  
Processing Techniques

Lung cancer is a serious health concern, which is also one of the major types of cancer that has a profound impact on the overall cancer mortality rates. The detection of lung cancer nodules is quite a challenge as the major challenge is the structure of the cancer nodules; here the cells are imbricated with each other. The prediction and classification of lung cancer is done by applying digital image processing techniques to the acquired input images of the nodules. This methodology also aids early detection which in turns reduces the criticality of the condition and provides scope for early intervention and treatment. The prediction methodology involves extracting several features of the lung cancer cell and then applying pattern-based prediction techniques. In recent times, owing to the fact that the time and execution parameters are very important aspects to detect the abnormality of the fast-spreading cancer cells, digital image processing techniques are being widely deployed. The fundamental factors of this research are the quality of image assessment and the precision of feature extraction. Following our proposed methodology, a clear picture of the region of interest is obtained which acts as a basis for the feature extraction process. Here an overall evaluation of the digital image processing techniques used by previous scholars for the finding and classification of lung cancer nodules have also been emphasised.

Detecting Thread Features Based on Digital Image Processing Techniques

2014 ◽  
Vol 889-890 ◽  
pp. 1107-1110
Author(s):  
Han Ming Cai ◽  
Pei Yao Wang ◽  
Xiao Mei Song
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Measurement Accuracy ◽  
Measuring Method ◽  
Image Processing Techniques ◽  
Basic Image ◽  
The Cost ◽  
Processing Techniques ◽  
Gauge Measurement

Thread features of the traditional measuring method mainly adopts working gauge measurement, due to limitations in the traditional thread features measurement accuracy is relatively low, the efficiency is low, the cost is high. The thread features detection method based on digital image processing techniques using CCD to obtain basic image of thread, processing the thread image, extracting thread outline, calculating thread features through the computer, improves the efficiency, saves the cost.

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