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SURVEY ON IMAGE PROCESSING METHODS USING THE FARMER PROFIT PRODUCTION M.Bhuvaneswari & R.Vinci Vinola Fatima College(Autonomous), Madurai ABSTRACT India is an agricultural country wherein about 70% of the population depends on agriculture. Agriculture has changed more in the past century than it has since farming began many millennia ago. Research in agriculture is aimed towards increase of productivity and food quality at reduced expenditure and with increased profit. Now day Computer technologies have been shown to improve agricultural productivity in a number of ways. One technique which is emerging as a useful tool is image processing. These techniques produce an output for the input image acquired through any of the imaging technique. The results are informative and supportive for farmers, agro based industries and marketers. It provides a timely support for decision making at an affordable cost. This paper presents a short survey on using image processing techniques to assist researchers and farmers to improve agricultural practices. Keywords Precision Agriculture; Image Processing; Profit for Farmer.
INTRODUCTION Now this year the continued demand for food with an increasing population, climate change and political instability. The agriculture industry continues to search for new ways to improve productivity and sustainability. This has resulted in researched from multiple disciplines searching for ways to incorporate new technologies and precision into the agronomic system. There is a need for efficient and precise techniques of farming, enabling farmers to put minimal inputs for high production. Precision agriculture is one of such techniques that is helping farmers in meeting both the above needs, precision agriculture can assist farmers in decision making about seed selection, crop production, disease monitoring, weed control, pesticide and fertilizers usage. It analyzes and controls farmer’s requirements using location specific information data and imagery techniques, Schellberg et al.(2008). In many parts of the world, Mainly in the rural areas this kind of data is inaccessible and the cost of procurement of these techniques is also not affordable by the farmers, Mondal and Basu(2009). The trends towards precision farming techniques are reliant on location specific data including the taking of multiple image databases. The use of image a survey of Image Processing Techniques for agriculture to be used for decision making IMAGE PROCESSING IN AGRICULTURAL CONTEXT Image processing techniques can be used to enhance agricultural practices by improving accuracy and consistency of processes while reducing farmers manual monitoring. Often it offers flexibility and effectively substitutes the farmer visual decision making. Image Processing term meaning image acquisition process of retrieving of a digital image from a physical source capture an image using sensors gray scale conversion process of converting. A color or multi channel digital image to a single channel where image pixel possess a single intensity value where image pixel possess a single intensity value image background, retrieving foreground objects Image enhancement improvement in perception of image details for human and machine analysis image histogram analysis pixel plot analysis in terms of peaks and valleys formed by pixel frequency and pixel intensities binary image segmentation foreground objects separation from background in a binary(black and white). Image color image segmentation image objects separation in color image, regions of interest image filtering process of distorting. An image in a desired was using a filter feature extraction process of defining a set of features or image characteristics that efficiently or meaningfully represent the information important for analysis and classification image registration process of
Page 2 and 3: A STUDY ON BIOMETRIC IMAGE PROCESSI
Page 4 and 5: Binarization converts gray scale im
Page 6 and 7: MOBILE SENSING ON INTERNET OF THING
Page 8 and 9: 4) Feedback applications These inco
Page 10 and 11: e said as a factor which is seen he
Page 12 and 13: Net, process the quickening, separa
Page 14 and 15: 1. Regular Sensing A portion of the
Page 16 and 17: CONCLUSION This paper is an overvie
Page 20 and 21: transforming different sets of data
Page 22 and 23: evaluating the food products qualit
Page 24 and 25: AN OVERVIEW OF CLOUD COMPUTING R. T
Page 26 and 27: CHARACTERISTICS OF THE CLOUD ‣ Th
Page 28 and 29: differ in the amount of control tha
Page 30 and 31: Improved performance o With few lar
Page 32 and 33: o Sharing documents leads directly
Page 34 and 35: CONCLUSION To summarize, the cloud
Page 36 and 37: Image Acquisition Image Pre- Proces
Page 38 and 39: ARTIFICIAL NEURAL NETWORK Descripti
Page 40 and 41: Disadvantages 1. Result transparenc
Page 42 and 43: Fig. 1: A Fingerprint Clarification
Page 44 and 45: FINGERPRINT ACQUISITION DEVICES Thi
Page 46 and 47: This strategy naturally creates art
Page 48 and 49: from every member (thumb, fore, and
Page 50 and 51: STORING AND VISUALIZTION OF 3D MODE
Page 52 and 53: MRI what could be compared to impro
Page 54 and 55: A STUDY ON DIGITAL IMAGE PROCESSING
Page 56 and 57: TECHNOLOGY The first animation film
Page 58 and 59: ROAD TRAFFIC SURVEILLANCE AND ACCID
Page 60 and 61: There are numerous crisis circumsta
Page 62 and 63: 2) Power supply The propose framewo
Page 64 and 65: B. Goal of Research To review break
Page 66 and 67: was done on two dataset VIRAT and M
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STUDY ON IMAGE PROCESSING IN SECURI
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OBJECT RECOGNITION Object recogniti
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CONCLUSION A banking locker securit
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INTRODUCTION In digital image proce
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3. TYPES OF DIGITAL CAMERA Com
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Most of the work done in image fore
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RAINFALL PREDICTION The paper is ab
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Also the cloud mask algorithm is us
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BIBLIOGRAPHY Watch "Intro
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INTRODUCTION In biological science,
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) Viral disease symptoms: Among all
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ANALYSIS ON NETWORK SECURITY S.Kart
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Data Integrity - assurance that dat
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those who know the particular key u
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CONCLUSION It's important to build
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A STUDY ON DIGITAL IMAGE PROCESSING
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Methodology This has two stages, fi
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REFERENCES 1) Digital Image Process
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VIRTUAL REALITY TECH AND WORKINGS A
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TABLE 2 PARTICULAR DIFFERS VIRTUAL
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The Big challenges in the field of
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STUDY ON REMOTE SENSING IN DIGITAL
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Scientists have made significant ad
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CONCLUSION Digital Image Processing
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By depiction, huge information in h
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Structured data denotes the tabular
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B. Algorithmic techniques Huge info
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Corridor laid out a strategy for bu
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subset can't be part and is for the
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REFERENCES 1. Alexandros Labrinidis
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