Aquaculture practices in mangrove area.MD. ZANE ALAM
Existing in a very rudimentary form for decades, brackishwater aquaculture in Bangladesh had been until recently nothing more than a casual activity in some tidal flood plain areas in the southwest part of the country.
In the early seventies, Bangladesh entered the world export market for shrimp. This crustacean, which was locally cheap and not even accepted as food by many locals, suddenly became a very high priced commodity. Since then much attention has been focused on increased production of this crustacean. The public sector efforts concentrated on the exploitation of shrimp from the sea by operating trawlers. The increasing demand and steadily rising prices of shrimp also caused a silent revolution in the brackishwater aquafarming sector: what was merely a casual activity of little economic significance, emerged as a multimillion taka farming industry in a few years time. Increased by leaps and bound, the shrimp culture activities were spread over a 26,000 ha area by the beginning of the current decade.
Surprising though, all this development took place in the private sector, without any extension, demonstration or new infrastructure support from the Government of Bangladesh. It is only since 1980, the starting year of the Second Five Year Plan, that brackishwater aquafarming has officially come to prominence.
In the Third Five Year Plan (1985–90) high priority has been given to brackishwater shrimp and fish culture. In view of the urgent socio-economic needs of the country (for domestic consumption, for export and for rural employment), the favourable ecological condition for shrimp culture and the existence of large areas with high production potential, this national priority for brackishwater aquafarming development is most justified. According to the Third Five Year Plan projection, brackishwater aquaculture will extend over 80,000 ha, as against 55,812 ha in 1984/85. By the end of the plan period, the production will expectedly increase to 34,000 MT, from a 1984/85 production of 9,000 MT. Nearly 18,000 MT of exportable shrimp would possibly come from aquaculture; this quantity would be 60 percent of the shrimp quantity projected for export in the terminal year of the Third Plan.
The present shrimp farming area is reported to have already far exceeded the Third Five Year Plan target. At the beginning of 1986, shrimp culture activities spread over 115,000 ha, distributed over several coastal districts (Annex A). The production per unit area is, however, still rather low. The need for increase of the production rate by intensification of the culture methodologies is currently being emphasized. Thereabove, the farmers are facing a number of technical problems, that need systematic analysis and appropriate solution. The planned Brackishwater Fisheries Research Station (BFRS) under the Fisheries Research Institute will hopefully meet the research requirements for the brackishwater aquaculture sector of the country.
Marine Scoops Guide To Coral Reefs (Part 1/3)Marine Scoop
A brief introduction to coral biology, reef formation and coral reproduction. Check out more at www.marinescoop.com and sign up to our weekly newsletter to receive parts II and III as soon as they are released! Part II will cover natural threats to coral reefs, coral bleaching, reef pollution, reef sedimentation, coral reef acidification and coral disease. Part III will cover overexploitation of reefs, destructive fishing practices on reefs, coral reef management and marine protected areas. Feel free to suggest another marine ecosystem to cover!
Aquaculture practices in mangrove area.MD. ZANE ALAM
Existing in a very rudimentary form for decades, brackishwater aquaculture in Bangladesh had been until recently nothing more than a casual activity in some tidal flood plain areas in the southwest part of the country.
In the early seventies, Bangladesh entered the world export market for shrimp. This crustacean, which was locally cheap and not even accepted as food by many locals, suddenly became a very high priced commodity. Since then much attention has been focused on increased production of this crustacean. The public sector efforts concentrated on the exploitation of shrimp from the sea by operating trawlers. The increasing demand and steadily rising prices of shrimp also caused a silent revolution in the brackishwater aquafarming sector: what was merely a casual activity of little economic significance, emerged as a multimillion taka farming industry in a few years time. Increased by leaps and bound, the shrimp culture activities were spread over a 26,000 ha area by the beginning of the current decade.
Surprising though, all this development took place in the private sector, without any extension, demonstration or new infrastructure support from the Government of Bangladesh. It is only since 1980, the starting year of the Second Five Year Plan, that brackishwater aquafarming has officially come to prominence.
In the Third Five Year Plan (1985–90) high priority has been given to brackishwater shrimp and fish culture. In view of the urgent socio-economic needs of the country (for domestic consumption, for export and for rural employment), the favourable ecological condition for shrimp culture and the existence of large areas with high production potential, this national priority for brackishwater aquafarming development is most justified. According to the Third Five Year Plan projection, brackishwater aquaculture will extend over 80,000 ha, as against 55,812 ha in 1984/85. By the end of the plan period, the production will expectedly increase to 34,000 MT, from a 1984/85 production of 9,000 MT. Nearly 18,000 MT of exportable shrimp would possibly come from aquaculture; this quantity would be 60 percent of the shrimp quantity projected for export in the terminal year of the Third Plan.
The present shrimp farming area is reported to have already far exceeded the Third Five Year Plan target. At the beginning of 1986, shrimp culture activities spread over 115,000 ha, distributed over several coastal districts (Annex A). The production per unit area is, however, still rather low. The need for increase of the production rate by intensification of the culture methodologies is currently being emphasized. Thereabove, the farmers are facing a number of technical problems, that need systematic analysis and appropriate solution. The planned Brackishwater Fisheries Research Station (BFRS) under the Fisheries Research Institute will hopefully meet the research requirements for the brackishwater aquaculture sector of the country.
Marine Scoops Guide To Coral Reefs (Part 1/3)Marine Scoop
A brief introduction to coral biology, reef formation and coral reproduction. Check out more at www.marinescoop.com and sign up to our weekly newsletter to receive parts II and III as soon as they are released! Part II will cover natural threats to coral reefs, coral bleaching, reef pollution, reef sedimentation, coral reef acidification and coral disease. Part III will cover overexploitation of reefs, destructive fishing practices on reefs, coral reef management and marine protected areas. Feel free to suggest another marine ecosystem to cover!
Future trends in aquaculture engineeringVikasUjjania
Aquaculture engineering is a multidisciplinary field of engineering and that aims to solve technical problems associated with farming of aquatic flora and fauna.
Fish location is the phenomenon of locating fish in the sea at a given area.
It also an indirect method where fishes are detected/found not directly detection the fish themselves but by some other factors like water temperature, turbidity, food availability etc.
Aquaculture continues to significantly expand its production, making it the
fastest-growing food production sector globally.
However, the sustainability of the sector is at stake due to the predicted effects of climate change that are not only a future but also a present reality.
In this Lecture, we review the potential effects of climate change on aquaculture production and its implications on the sector ’ s sustainability.
Various elements of a changing climate, such as rising temperatures, sea-level
rise, diseases and harmful algal blooms, changes in rainfall patterns, the uncertainty of external inputs supplies, changes in sea surface salinity, and
severe climatic events have been discussed. Furthermore, several adaptation options have been presented as well as some gaps in existing knowledge that
require further investigations.
Dolphins are appealing intelligent sea creatures well known for their love of play and friendliness to humans
Despite their appearance , dolphins are not fish but mammals ; air breathing, warm blooded animals whose young feed on their mother’s milk
The Journal of Marine Biology & Oceanography (JMBO) promotes rigorous research that makes a significant contribution in advancing knowledge for marine sciences. JMBO includes all major themes pertaining to organisms in the ocean or other marine or brackish water bodies.
Management of ornamental fish farm.
Pond fish keeping
Pond Construction
Sitting a pond
Site of a pond
Equipment
Stockings of pond with fish
Invertebrates and amphibians
Pond maintenance feeding
Texture Classification of Sea Turtle Shell based on Color Features: Color His...ijaia
A collaborative system for cataloging sea turtles activity that supports picture/video content demands
automated solutions for data classification and analysis. This work assumes that the color
characteristics of the carapace are sufficient to classify each species of sea turtles, unlikely to the
traditional method that classifies sea turtles manually based on the counting of their shell scales,
and the shape of their head. Particularly, the aim of this study is to compare two features extraction
techniques based on color, Color Histograms and Chromaticity Moments, combined with two classification
methods, K-nearest neighbors (KNN) and Support Vector Machine (SVM), identifying
which combination of techniques has a higher effectiveness rate for classifying the five species of
sea turtles found along the Brazilian coast. The results showed that the combination using Chromaticity
Moments with the KNN classifier presented quantitatively better results for most species
of turtles with global accuracy value of 0.74 and accuracy of 100% for the Leatherback sea turtle,
while the descriptor of Color Histograms proved to be less precise, independent of the classifier.
This work demonstrate that is possible to use a statistical approach to assist the job of a specialist
when identifying species of sea turtle.
Future trends in aquaculture engineeringVikasUjjania
Aquaculture engineering is a multidisciplinary field of engineering and that aims to solve technical problems associated with farming of aquatic flora and fauna.
Fish location is the phenomenon of locating fish in the sea at a given area.
It also an indirect method where fishes are detected/found not directly detection the fish themselves but by some other factors like water temperature, turbidity, food availability etc.
Aquaculture continues to significantly expand its production, making it the
fastest-growing food production sector globally.
However, the sustainability of the sector is at stake due to the predicted effects of climate change that are not only a future but also a present reality.
In this Lecture, we review the potential effects of climate change on aquaculture production and its implications on the sector ’ s sustainability.
Various elements of a changing climate, such as rising temperatures, sea-level
rise, diseases and harmful algal blooms, changes in rainfall patterns, the uncertainty of external inputs supplies, changes in sea surface salinity, and
severe climatic events have been discussed. Furthermore, several adaptation options have been presented as well as some gaps in existing knowledge that
require further investigations.
Dolphins are appealing intelligent sea creatures well known for their love of play and friendliness to humans
Despite their appearance , dolphins are not fish but mammals ; air breathing, warm blooded animals whose young feed on their mother’s milk
The Journal of Marine Biology & Oceanography (JMBO) promotes rigorous research that makes a significant contribution in advancing knowledge for marine sciences. JMBO includes all major themes pertaining to organisms in the ocean or other marine or brackish water bodies.
Management of ornamental fish farm.
Pond fish keeping
Pond Construction
Sitting a pond
Site of a pond
Equipment
Stockings of pond with fish
Invertebrates and amphibians
Pond maintenance feeding
Texture Classification of Sea Turtle Shell based on Color Features: Color His...ijaia
A collaborative system for cataloging sea turtles activity that supports picture/video content demands
automated solutions for data classification and analysis. This work assumes that the color
characteristics of the carapace are sufficient to classify each species of sea turtles, unlikely to the
traditional method that classifies sea turtles manually based on the counting of their shell scales,
and the shape of their head. Particularly, the aim of this study is to compare two features extraction
techniques based on color, Color Histograms and Chromaticity Moments, combined with two classification
methods, K-nearest neighbors (KNN) and Support Vector Machine (SVM), identifying
which combination of techniques has a higher effectiveness rate for classifying the five species of
sea turtles found along the Brazilian coast. The results showed that the combination using Chromaticity
Moments with the KNN classifier presented quantitatively better results for most species
of turtles with global accuracy value of 0.74 and accuracy of 100% for the Leatherback sea turtle,
while the descriptor of Color Histograms proved to be less precise, independent of the classifier.
This work demonstrate that is possible to use a statistical approach to assist the job of a specialist
when identifying species of sea turtle.
This presentation contains a case study on the project WildME which is based on computer vision and is helping in detecting aminals all across the world.
It is an introductory slide for pattern recolonization. This presentation was quit emotional for me because it was the last academic presentation in Green University of Bangladesh. For that i have used a sad emo at the first of the slide.
Vision based entomology how to effectively exploit color and shape featurescseij
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of
agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the
diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various kinds
of interactions between humans and insects. There have been several attempts to create a method to
perform insect identification accurately. Great knowledge and experience on entomology are required for
accurate insect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. We propose an automatic insect identification framework that can identify
grasshoppers and butterflies from colored images. Two classes of insects are chosen for a proof-ofconcept.
Classification is achieved by manipulating insects’ color and their shape feature since each class
of sample case has different color and distinctive body shapes. The proposed insect identification process
starts by extracting features from samples and splitting them into two training sets. One training
emphasizes on computing RGB features while the other one is normalized to estimate the area of binary
color that signifies the shape of the insect. SVM classifier is used to train the data obtained. Final decision
of the classifier combines the result of these two features to determine which class an unknown instance
belong to. The preliminary results demonstrate the efficacy and efficiency of our two-step automatic insect
identification approach and motivate us to extend this framework to identify a variety of other species of
insects.
Through the Eyes of Animals: Measuring Animal Vision” In talking about the science of the eye and vision in life science and biology classes, many students are intensely interested in animal vision. They often ask, "What do animals see?" Dr. Mills-Henry presented a way to capitalize on that interest by demonstrating a lab on testing animal vision using easy-to-obtain invertebrate model organisms.
x ray microscopic image analysis to detect infestations caused by insects in ...mahnoorbaig11301
Principle of Operation:
X-ray microscopes use short-wavelength X-rays, which have high energy, to penetrate materials.When X-rays pass through an object, they interact with the material, and the degree of absorption depends on the material's density and composition.
Imaging Process:
X-ray microscopes generate images by detecting variations in X-ray absorption as the rays pass through the specimen.Dense regions absorb more X-rays and appear darker in the images, while less dense areas allow more X-rays through, appearing brighter.
Resolution:
X-ray microscopes can achieve high resolutions, allowing scientists to study structures at the nanoscale.This level of detail is crucial for examining biological specimens, materials, and other samples.
Applications:
Biological Research:
X-ray microscopes enable non-destructive imaging of biological samples, providing insights into cellular and subcellular structures.
Material Science:
They are used to study the internal composition, defects, and characteristics of materials such as metals, ceramics, and polymers.
Geology and Environmental Science:
X-ray microscopy aids in analyzing geological samples and studying environmental materials.
Types of X-ray Microscopes:
Transmission X-ray Microscope (TXM): X-rays pass through the specimen to create an image.
Scanning X-ray Microscope (SXM):
A focused X-ray beam scans the specimen, creating detailed 2D and 3D images.
Synchrotron Radiation:
Some X-ray microscopes use synchrotron radiation, produced by particle accelerators, to generate intense and focused X-ray beams for improved imaging.
Advantages:
Non-destructive:
X-ray microscopy allows imaging without altering or damaging the specimen.
High Resolution:
Capable of revealing fine details at the microscopic and nanoscopic levels.
Limitations:
Sample Thickness:
Thick samples may obscure details as X-rays are absorbed.
Radiation Damage:
Prolonged exposure to X-rays may damage biological samples.
Human-Wild animal conflict is the major problem in the forest borders with large wild animal herds. Human conflicts with wild animals often occur, along with the narrowing of the wild animal habitat due to industrial and residential interests. The negative impacts of human wild animal conflict is on a large scale slaughter of wild animals. This problem which leads to crop damage, human death and injuries caused by wild animals, and wild animals being killed by humans. Wild animal Intrusion has been on the rise in the forest border areas with herds of wild animals straying into human habitation and creating a great loss to their properties. The surveillance and tracking of wild animals are difficult due to their size and nature of movement. Prevention system for indications of human wild animal conflict is absolutely necessary. So an intelligent electronics system is necessary which can be affixed to avoid the human-wild animal conflicts. In this paper, an automated system to detect the intrusion of wild animals into the human habitat in forest borders is proposed. Basic idea behind this work is to generate the sound signal which can be inaudible to human and irritating for wild animal. Such instrument can be mounted on forest borders so that wild animal herds will go back into the forest. The proposed is very efficient with good computation power and low cost. Pavithra. M. H | Nivetha. R | Haritha. M | Sandra Karunya | Madhan Gopi"Scaring Animals using Assembler Language" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11446.pdf http://www.ijtsrd.com/engineering/computer-engineering/11446/scaring-animals-using-assembler-language/pavithra-m-h
ijerst offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal. International Journal of Engineering Research and Science & Technology (IJERST) is an international online journal in English published Quarterly. All submitted research articles are subjected to immediate rapid screening by the editors.
ijerst offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. International Journal of Engineering Research and Science & Technology (IJERST) is an international online journal in English published Quarterly. All submitted research articles are subjected to immediate rapid screening by the editors, in consultation with the Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Francesca Gottschalk - How can education support child empowerment.pptx
Autumated image processing system
1. A seminar on
AN AUTOMATED IMAGE PROCESSING SYSTEM FOR
IDENTIFICATION OF FISH SPECIES LABEO BATA
FRM-591
2. Contents of my seminar:
Introduction
Need of fish identification
Challenges of identification
History of an image recognition
Objective of my thesis
Systematic position
Methodology of an automated image recognition system
Data collection
Image preprocessing
Features extraction
Features extraction technique
Classification
Fish identification
Advantage of an automated image recognition system
Future scope of the research
Conclusion
References
3. INTRODUCTION:
Fish species identification is traditionally based on external
morphological features.
This process of identification is follow well trained fisherman and
fishery expert.
In case of common people it is very hard work to identified all
kinds of fishes.
Most recently An automated Image Recognition System was
developed to identify fishes.
In this method user provided a photograph of a fish as input and
the software identifies the fish to a taxonomic level.
4. NEED OF FISH IDENTIFICATION
World has more than 32,500 fish species. Among them some are edible and
some are extremely poisonous.
Many of people died every year because they do not identify the poisonous
and non-poisonous fish.
So it is essential to identify properly whether it is harmful or not.
Fishes like Puffer fish, Lion fish, and some of the Eels are extremely
dangerous to eat.
To avoid this type of poisonous fishes we need to have proper knowledge of
identification.
There are many others reason where proper indentified of fish is needed.
This are -
1. In fish processing industries the first step is to identify the fishes and
sorted according to their commercial importance. Because the value of the
product depends on quality and types of fishes. If some unknown species is
processed by mistake then the whole product should be damaged.
2. Fish identification is not only helpful to fisheries industries, it also helps
the consumers. There are several fishes in the market which are quite similar on
their appearance and huge confusion among them. Sometimes consumers are
cheated by the seller due to lack of knowledge about fishes.
3. The price of the Ornamental fish depends on sex of the fishes. So proper
identification is highly profitable for the business,
5. Identification of fish is more difficult than any other organism.
Teleost species are the largest category among vertebrate
animals.
Their numbers reached more than 32,500.
Fishes show their diversity among themselves with shape, size
and color. So it is very hard work to recognition the fish species.
Some difficulties are-
Challenges of identification of fish
1) Not easily visible- It is very difficult to identify a fish
under water as it is not possible to see clearly
morphological and anatomical characters.ii) Perishable-Fishes are highly perishable object. After removing
fishes from water, it started to degrade so quickly. The
anatomical and morphological character spoiled. So it becomes
very difficult to identify particular species
iii) Similar shape- There are several fishes in the world which are
similar shape and size. It makes difficult to identify the fishes.iv)Unidentified species- Till now there is a huge unexploited
underwater area and many fishes are totally unknown to the
scientists.
v) Hybridization- Sometime cross breeding is occur among the
underwater species and new types of species with new characters
are come out.
6. History of Image Recognition:-
The evolution of fish began about 530 million years ago.
During this time people caught fishes only for food purposes
without knowing any name, and mistakenly having some poisonous
fishes then accident may occur.
After that people trying to identifying the edible fishes and till
now the identifying process is continue.
Now identifying of fish through computer system is developed
recently around 60 years ago.
Computer scientists are always trying to extract meaning of the
image by machine learning.
7. 1) In 1959 Russell Kirsch and his colleagues develops a system that
transforms visual images into numbers, which machine could understand.
2) In the year 1982 David Man developed a system which can detect edges,
curves, corners of an image.
3) A Japanese computer scientist, Fukushima built a self-organizing
artificial network which recognize the patterns of an image. The network
consists of several convolutional layers which can identify shape of an
image.
4) In 1997 Jitendra Malik tried to convert a images into sensible parts using
a graph theory algorithm.
8. Objective of my thesis:
Labeo bata commonly known as bata or bangon is one of the
most important target species for small scale fisheries.
L. bata is commercially important and great demand in the
market because of its high nutritional value and good taste.
Object of my research tropic is to identify the Label bata
through an automatic image processing system.
10. Morphological description:
Dorsal profile is more convex than that of abdomen. Body elongated, A pair of
small maxillary barbells is hidden inside the labial fold. Dorsal originates midway
between snout tip and anterior base of anal. Pelvic originate slightly nearer to
snout tip than caudal base. Bluish or darkish on upper half, silvery below. scales
on the lateral line is 38 and 40 respectively.
Habit and habitat:
Labeo bata is a freshwater fish found in small rivers, canals, ponds and
ditches. Its food are crustaceous and insect larvae in early stages. In adult stage
rotten plant, algae and plankton are eaten.
Breeding:
Size at first sexual maturity is 14.12 and 14.60 cm in male and female.
Spawning season varies from June to October, average fecundity was 192785.
11. Methodology of an Automated Image
Recognition System:-
There are mainly 5 steps of an automated image recognition
system. This are-
Data collection Image
prepossessing
Image
segmentation
Classification
Feature extraction
12. Data collection:
Data collection is an important part of this system. Here collection
of data means captures the images of fishes. There is no particular
limit of data collection. More data means more accurate result.
However, for a good accuracy minimum 300 picture needed for
each species. There are some process of data collection.
1) Data should be collected randomly.
2) Resolution should be same for each image.
3) Picture must be taken from 900 angle.
4) Full body of the fish have to be captured.
5) Caudal fin arranged in relaxed position.
6) Fishes must be photographed sideway.
13. Image preprocessing:
Image pre-processing is nothing but a image is prepared
and ready for next step. Image preprocessing can be
done by-
1. Sorting and Labeling of the images.
2. Colour intensity normalization
3. Enhances the edges of an image.
4. Reduces the blur of an image..
5. Rotation of an images into same direction.
6. Resizes the images into a normalized range.
7. Horizontal and vertical brightness normalization.
14. Feature extraction:-
Features define the behavior of an image and Feature
extraction is the main part of an image recognition system.
The main purpose of feature extraction is to detect largest set
of features of a species which are same for a similar species but
different from another species.
In this process relevant features were extracted from object’s
image which is form ‘feature vectors.’
Then these ‘feature vectors’ were used by classifiers to
recognize the input data for target output data.
The classifier is classify between different classes by looking
at these features and make easy to distinguish between two
classes.
15. Some feature extraction technique.
1. Texture feature extraction using LBP:- The term texture generally refers to
texels, which contains several pixels. LBP described the texture of an image.
In this process the image is dividing into several small regions from which the
features are extracted and considers the result as a binary number.
2. Geometric parameter using contour feature :- Contours detection is a
process can be explained simply as a curve joining to all continuous points.
3. Colour feature using Colour Histogram:- Colour Histogram is the most
widely used technique for extracting the colour feature of an image. It
represents the frequency distribution of colour bins of an image
16. Classification:
The main purpose of the classification is to categorize the input
images depends on their features.
It is machine learning approach which the computer program learns
from the input datasets.
On the basis of features, classifier categorized the input data to
specific type of category.. At first, the classifier was trained with
training dataset. Accuracy of the classifier depended on the quality of
training data set.
17. Some classifier are
Artificial Neural Network (ANN )- Biologically inspired computer
programs. ANNs gather their knowledge by detecting the patterns
and relationships in data and learn through experience, not from
programming.
K-Nearest Neighbor (KNN-) K nearest neighbors is a simple
algorithm that stores all available classes and classifies new classes
based on a similarity measure.
Support Vector Machine (SVM) : It is a classifier formally defined
by a separating hyperplane. Hyper plane is a one dimensional or
two-dimensional boundary which separate 2 classes.
18. Fish identification:
The application was built on MATLAB 2018a APP designer.
It was mainly graphical user interface model.
The application has a button of ‘Load Image’ to input an unknown
image.
The image was displayed on the upper portion of the application.
It has a ‘Test Image’ button to identify the image of fish. After
pressing the ‘Test Button’ the predicted result will be shown below
the ‘Test Button’.
The accuracy rate or quality of prediction will be shown on bottom
left corner of the system.
19. Advantages of Image Recognition through
automatic image recognition System:
Response Time- Response time defines how quickly a result is obtained.
Traditional tools require more time to identify fish because it is processed through
several steps. But Automatic image identification system works on very low
response time. Therefore, it is used in practical field.
Accuracy-Accuracy measures the error rate of an identification system.
Sometimes manual identification is not so accurate because the chance of mistake.
But automated computer based recognition system has more accuracy than any
other identification tools.
Parts of body: In case of manual identification it is not possible to identify a
fish through its body part. Whereas through automatic image processing system it
is possible to identify species by its body parts or photographs.
20. The present study on “An automated image recognition system for identification
of Indian minor carps will be helpful to all label of person who engaged fishery
sector. The major focus in this field-
Identification of live underwater fishes through video footage.
Automatic Sorting of fishes according to the species, sex and size.
Implementations of the system into mobile device so that anyone can access
the application at anywhere anytime like QR barcode.
The system needs to be implemented in a world-wide-web based system so
that people can share global fish information.
FUTURE SCOPE OF RESEARCH
21. The development of an automated image
recognition system (software) may be a stepping
stone in the field of fish taxonomy.
But it has to cross a long journey to fulfill the
requirement of fish folks of the world. Then it will be
helpful for the people who are ignorant about the fish
species, its’ variety and its identification.
CONCLUSION
22. References:-
www.google.com
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computer-vision-and-convolutional-neural-networks-8fe8aacc79f3
Texture Feature. Retrieved 31 July (2019), from
https://support.echoview.com/WebHelp/Windows_and_Dialog_Boxes/Dialog_Box
es/Variable_propert
Identification of Fish Species based on Image Processing and Statistical
Analysis Research(Lian Li , Jinqi Hong)
Shape-Based Fish Recognition Using Neural Network.(Purti Singh,Deepti
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https://medium.com/machine-learning-101/chapter-2-svm-support-vector-machine-
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