biomarker

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Fish Liver&& Gills microscopic image as Biomarker for water guality

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FISH LIVER AS BIOMARKER FOR WATER QUALITYWATER QUALITY

Presented by:Asmaa Hashem , Master student

Supervised by :Dr Nashwa El-Bendaryprof Aboul Ella Hassanien

Scientific Research Group in Egyptwww.egyptscience.net

2 Introduction1

Content

2 Problem definition && Objective

Proposed system modelProposed system model3

Current Task4

Introduction

The monitoring of water quality is a great challenge today. To

carry out chemical analysis continuously is complex and

expensive, and also provides limited data about the chemical

compounds which ignores the influence of those excluded in

the analysis.

Fish Liver observed microscopically showed increasing

degrees of damage in the tissues in correlation with the quality

of water. So we use the fish liver as a biomarker for water

quality.

Problem definition

Fish Liver and Gills as biomarker on water quality Based on Microscopic Images

Objective

presents an image classification approach to automate the

process of assessing water quality by examining and

classifying different Fish liver histopathology.

Input Microscopic gills image

Pre-processing Stage

Color- and Texture-Based Image Enhancement ,segmentation,The Morphological and

Input Microscopic liver Image

The Proposed system Model

The Morphological and Logical operation

Feature Extraction Stage

Classification Stage

Testing Stage and detect similar images

Result( water Quality or not)

The Proposed system Model

PhasePhase 11.. PrePre--processingprocessing phasephase

Pre-Processing phase takes dataset as a image data input

Then ,the contrast enhancement is performed. Thus, contrast of a

microscopic image in a given Grey level texture descriptors modelmicroscopic image in a given Grey level texture descriptors model

the spatial relationship of a pixel and its neighbors.

In pre-processing stage, the thresholding is performed to

microscopic images. The threshold value must be selected

appropriate to image. If the threshold value is well selected,

threshold will yield good visualization and increase the accuracy

and efficiency of the subsequent processing.

The Proposed system Model

PhasePhase 11.. PrePre--processingprocessing phasephase

In pre-processing stage, used to extract the Shape Feature

vector. The Morphological operations produce an output

image in which each pixel is based on the comparison of the

input image and its neighborhood

Morphological operations on query image are two type:

The Dilation operation adds pixels to the boundaries of the objects

the Erosion operation removes pixels from the object boundaries.

The Proposed system Model cont…

PhasePhase 22::Feature extraction stage: In this stage, we use the

method derives a set of functions that make use of the

central moments of pre-processed image for characterize the

shape of each image . The output of these is independent of

any translation, rotation or mirror image

PhasePhase 33 Classification stage: In this stage is used for

classification of features extracted feature extraction stage.

For this aim, a database was constructed from The training

The Proposed system Model cont…

PhasePhase 44 Testing stage: In testing stage, the rest of the database

was used for testing of the proposed system based

classification of fish microscopic images.

Current Task

Analysis of the collected data . And preparing this

data for processing

Thank youThank you

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