An application of image processing techniques for detection of diseases on brinjal leaves using k-means clustering method

2019 ◽

Vol 1 (1) ◽

pp. 16-24

Author(s):

Atriyan Trisnawan ◽

Wahyudi Hariyanto ◽

Syahminan

Keyword(s):

Image Processing ◽

Oryza Sativa L ◽

Extraction Process ◽

Clustering Method ◽

Important Food ◽

Image Processing Techniques ◽

Daily Food ◽

Grinding Tool ◽

Processing Techniques

Rice plants (Oryza Sativa L.) are important food crops that have become a staple food for more than half of the world's population. In Indonesia rice is the main commodity in supporting community food. The process of processing rice into rice is done in two ways, namely the processing of pulverized and modern processing using a grinding tool. Rice is an important component in daily food. There are several types on the market, namely: fragrant pandan rice, IR 64, IR 42, C 4, and others. With the variety of forms and types of rice on the market, there are many weaknesses that humans have in perceiving the classification of rice using the senses of vision. Therefore, digital image processing techniques are needed to help analyze the type of rice. This study aims to analyze the type of rice using the K-Means Clustering method based on RGB colors. Before the K-Means calculation, the RGB color feature extraction process must be carried out to get the red value, green value, blue value in each image. The results of this study found that image processing to determine the type of rice using the k-means clustering method can help users to know the type of rice.

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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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