MonVoix-An Android Application for the acoustically challenged people

Human communication is the most valuable foundation in developing a cooperative environment for sharing information and knowledge by interactive sessions. Normal individual vocalizes his views through shared intentions like facial expressions and hand gestures. People with acoustical disabilities are obligated to rely on interpreters for day-to-day conversations. Interpretation of various Sign Languages is important as it will shorten the social drift and act as an agent of communal integration. This paper proposes an Android Application for a coherent interpretation of Sign Languages. MonVoix- a French remark for my voice, would act as a boon for the deaf and the mute by completely eliminating the requisite of a human interpreter. This approach utilizes a user’s Smartphone camera to capture a series of hand gestures and convert the image file to the corresponding message and audio using image processing techniques and database emulation for identification of image.

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Identification of Feasibility of Canned Based Foods Image Processing Techniques Using Thresholding

Buletin Ilmiah Sarjana Teknik Elektro ◽

10.12928/biste.v3i1.1608 ◽

2021 ◽

Vol 3 (1) ◽

pp. 10

Author(s):

Ilhamsyah Muhammad Nurdin ◽

Abdul Fadlil

Keyword(s):

Image Processing ◽

Visual Observation ◽

Android Application ◽

File Transfer Protocol ◽

File Transfer ◽

Canned Food ◽

Image Processing Techniques ◽

Accuracy Level ◽

Processing Techniques

Eye sight is sometimes deceptive, especially in determining the quality of a canned food, so it is necessary to use technology that resembles human visual observation, namely in the form of an application. The process to detect the quality of canned food uses image processing methods, especially thresholding, which is then designed so that the application is able to determine the quality of canned food with the help of the MATLAB GUI which detects and then sends it from making the MATLAB GUI on the Laptop to Android using FTP (File Transfer Protocol). At the end of the process, it is marked with known good and bad quality of canned food with an android application that has been specially designed with an accuracy level of 84% with a thresholding value of 70.

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Plant Leaf Disease Detection using Image Processing

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.f4597.059720 ◽

2020 ◽

Vol 9 (7) ◽

pp. 409-414

Keyword(s):

Image Processing ◽

Support Vector Machine Classifier ◽

Value Added ◽

Support Vector ◽

Gray Level ◽

Early Detection Of Disease ◽

Image Processing Techniques ◽

The People ◽

The Social ◽

Processing Techniques

Agriculture, the primary way to produce the food to the people besides its value added to the economy of the country’s gross domestic product. Plants are affected to various diseases and early detection of disease has to be done in order to reduce the social and economical loses. Nowadays farmers are not aware of the type of diseases that affect the plants and the respective measures that have to be taken in order to reduce the effect. This paper focuses on the technique that detects the disease using image processing techniques and providing the measures to the farmers to overcome the disease. The technique is based on the K means clustering which is used to segment the image after that the feature extraction is done based on the Gray level Coocurrence matrix approach then the Support Vector Machine classifier is used to classify the disease with the trained data. We have calculated the percentage of leaf affected and the measurement is done based on it. Here along with disease name its symptoms and measurement are shown

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Three-Dimensional Structure of Rotavirus-Fab Complex

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100179944 ◽

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.

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

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit2063211 ◽

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.

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