scholarly journals Detection of Dental Diseases using Classification Algorithms

2019 ◽  
Vol 8 (3) ◽  
pp. 4485-4489
Keyword(s):  
Correct Diagnosis ◽  
Wiener Filter ◽  
Classification Algorithms ◽  
Threshold Region ◽  
Image Processing Techniques ◽  
Image Edge Detection ◽  
Dental Diseases ◽  
Image Edge ◽  
Processing Techniques ◽  
Teeth Abnormalities

Dental diseases may be caused if the food taken stays in the corners of the mouth. It is important to analyze the dental images to improve and qualify medical images for correct diagnosis. The teeth abnormalities may fall into different categories such as dental implants, gum diseases, crack, bone grafting, and root canal. This work aims to identify the type of abnormalities using classification algorithms — image Processing Techniques, namely Enhancement, Segmentation, and Classification involved in this process of dental disease detection. Decorrelation Stretch, Wiener Filter, and Contrast Enhancement are some of the enhancement techniques which were used to improve the clarity of a dental image. Edge Detection, Otsu's Threshold, Region-Based Segmentation, and Texture filters are few of the image segmentation techniques. These are used to identify the defected area of an image, and then the type of abnormalities was classified using K-NN and SVM.

The Design of the Detection and Localization of the Color Image for the Location of Road Traffic Signs

2011 ◽  
Vol 301-303 ◽  
pp. 143-146 ◽  
Author(s):  
Xin Ma ◽  
Hong Li Li
Keyword(s):  
Edge Detection ◽  
Road Traffic ◽  
Color Image ◽  
Feature Space ◽  
Threshold Region ◽  
Traffic Signs ◽  
Image Edge Detection ◽  
Image Area ◽  
Image Edge ◽  
Intelligent Recognition

An intelligent recognition algorithm of the combination of image edge detection and image area segmentation is designed in this paper. The image edge detection adopts the edge detection method of color feature space. The color multi-threshold region segmentation method is used the image area segmentation. The algorithm is mainly used for the detection and location of city road traffic signs. Some traffic scene images are processed by this algorithm. The simulation results show that the combination algorithm has better segmentation ability. It is helpful to realize the intelligent recognition of road traffic signs.

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

Rice Panicle Blast Detection and Grading Based on Image Processing Techniques

2019 ◽  
Vol 7 (5) ◽  
pp. 165-168 ◽  
Author(s):  
Prabira Kumar Sethy ◽  
Swaraj Kumar Sahu ◽  
Nalini Kanta Barpanda ◽  
Amiya Kumar Rath
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Panicle Blast ◽  
Processing Techniques

Identification of Cucumber Leaf Disease using Image Processing Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 1493-1499
Author(s):  
Shrutika.C.Rampure . ◽  
Dr. Vindhya .P. Malagi ◽  
Dr. Ramesh Babu D.R
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Leaf Disease ◽  
Processing Techniques

Character Reorganization and Categorization using Hybrid Algorithms by Scanned Documents

2019 ◽  
Vol 8 (6S2) ◽  
pp. 943-948
Keyword(s):  
Research Work ◽  
Hybrid Algorithms ◽  
Research Topic ◽  
Image Processing Techniques ◽  
Digital Books ◽  
Otsu Method ◽  
Challenging Research ◽  
Processing Techniques ◽  
Scanned Documents ◽  
Day By Day

Detection and reorganization of text may save a lot of time while reproducing old books text and its chapters. This is really challenging research topic as different books may have different font types and styles. The digital books and eBooks reading habit is increasing day by day and new documents are producing every day. So in order to boost the process the text reorganization using digital image processing techniques can be used. This research work is using hybrid algorithms and morphological algorithms. For sample we have taken an letter pad where the text and images are separated using algorithms. The another objective of this research is to increase the accuracy of recognized text and produce accurate results. This research worked on two different concepts, first is concept of Pixel-level thresholding processing and another one is Otsu Method thresholding.

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