scholarly journals Subject Review: Diagnoses cancer diseases systems for most body's sections using image processing techniques

2021 ◽  
Vol 6 (3) ◽  
pp. 056-062
Author(s):  
Dena Nadir George ◽  
Haitham Salman Chyad ◽  
Raniah Ali Mustafa
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Medical Imaging ◽  
Image Processing Techniques ◽  
Classification Feature ◽  
Segmentation Methods ◽  
Comprehensive Survey ◽  
Segmentation Image ◽  
Processing Techniques ◽  
Cancer Diseases

Medical imaging has become an important part of diagnosing, early detection, and treating cancers. In this paper, a comprehensive survey on various image processing techniques for medical images specifically examined cancer diseases for most body sections. These sections are Bone, Liver, Kidney, Breast, Lung, and Brain. Detection of medical imaging involves different stages such as classification, segmentation, image pre-processing, and feature extraction. With regard to this work, many image processing methods will be studied, over 10 surveys reviewing classification, feature extraction, and segmentation methods utilized image processing for cancer diseases for most body's sections are clearly reviewed.

scholarly journals A Study on Image Segmentation Method for Image Processing

2021 ◽  
Author(s):  
S. Prabu ◽  
J.M. Gnanasekar
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Surveillance System ◽  
Vital Role ◽  
Important Process ◽  
Image Processing Techniques ◽  
Segmentation Methods ◽  
And Performance ◽  
Segmentation Image ◽  
Processing Techniques

Image processing techniques are essential part of the current computer technologies and that it plays vital role in various applications like medical field, object detection, video surveillance system, computer vision etc. The important process of Image processing is Image Segmentation. Image Segmentation is the process of splitting the images into various tiny parts called segments. Image processing makes to simplify the image representation in order to analyze the images. So many algorithms are developed for segmenting images, based on the certain feature of the pixel. In this paper different algorithms of segmentation can be reviewed, analyzed and finally list out the comparison for all the algorithms. This comparison study is useful for increasing accuracy and performance of segmentation methods in various image processing domains.

scholarly journals PENGENALAN HURUF LATIN PADA ANAK USIA DINI DENGAN PENERAPAN METODE BACKPROPAGATION

2021 ◽  
Vol 2 (2) ◽  
pp. 130-137
Author(s):  
Slamet Riyadi ◽  
Zilvanhisna Emka Fitri ◽  
Arizal Mujibtamala Nanda Imron
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Early Childhood ◽  
Feature Extraction ◽  
Image Processing Techniques ◽  
Total Data ◽  
Backpropagation Method ◽  
Testing Accuracy ◽  
Processing Techniques ◽  
Pixel Mapping

Early childhood has difficulty remembering Latin letters or Roman characters than adults. Some of the factors that cause it are cognitive development, motivation, interest in learning, emotions and environmental factors. To overcome this, an innovative media is needed so that children can easily remember Latin letters. One of the innovative media applies digital image processing techniques and artificial intelligence. The fonts used are 10 types of letter models with image processing techniques such as preprocessing, binaryization, pixel mapping and creating vector as feature extraction.  While the artificial intelligence used is the backpropagation method. The total data is 208 letter images with 625 input features with 500 epochs, the best learning rate used by the system is 0.025 so that the best training accuracy is 93.96% and testing accuracy is 92.31%.

scholarly journals CHARACTERISATION OF TABLETS FOR DEFECT IDENTIFICATION USING IMAGE PROCESSING TECHNIQUES FOR QUALITY CONTROL IN PHARMACEUTICAL INDUSTRY

2017 ◽  
Vol 10 (11) ◽  
pp. 270
Author(s):  
Durga Karthik ◽  
Vijayarekha K ◽  
Surya K
Keyword(s):  
Image Processing ◽  
Quality Control ◽  
Feature Extraction ◽  
Pharmaceutical Industry ◽  
Color Variation ◽  
Defect Identification ◽  
Image Processing Techniques ◽  
Manufacturing Line ◽  
Area And Perimeter ◽  
Processing Techniques

  Objective: Our aim is to characterize the parameters for identifying defective tablets from the manufacturing line using image processing techniques.Methods: Manufactured tablets might have defects such as broken chips, missing tablet, and color variation. Images of tablets are captured using machine vision camera. The features are detected using feature extraction for a tablet without defects and are stored in a database. The stored details are used for identifying defective tablets during manufacturing.Results: The characteristics such as color, shape, number of pills, area, and perimeter of the normal tablets without defects were extracted.Conclusion: The defective tablets can be identified by comparing the characteristics stored in the database and can be removed effectively.

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