image processing research paper abstract

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REVIEW PAPER ON OVERVIEW OF IMAGE PROCESSING AND IMAGE SEGMENTATION

2013, IJRCAR

Abstract— Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. Image processing usually refers to digital image processing, but optical and analog image processing also are possible. This article is about general techniques that apply to all of them. The acquisition of images (producing the input image in the first place) is referred to as imaging. Image segmentation is a process of partitioning an image into sets of segments to change the representation of an image into something that is more meaningful and easier to analyze.

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Ravindra Rathore

Abstract- Today Ceramic Tile is mostly used in construction of floor at home, offices and shops and many other places. For user needs the ceramic tile industry demand increase, thus tile industry also increases the production, but the quality maintaining or quality control is also an important factor. This factor is directly related the production of ceramic tile. If quality is maintaining manually, it takes lots of time and some minor defect not finding by this process. In this paper we find corners defects of the ceramic tiles. We use image processing and Inverse Trigonometric Function. The angle of each corner square ceramic tile is equal to 90˚ means it is normal. Our proposed algorithm is classified in Upgraded Automatic Quality Maintaining Machine (UAQMM). By proposed algorithm we increase the efficiency rate and decrease the total computational time.

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Image processing is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within electronics engineering and computer science disciplines too. Image Processing is a technique to enhance raw images received from satellites, space probes, aircrafts, military reconnaissance flights or pictures taken in normal day-to-day life from normal cameras. The field is becoming powerful and popular because of technically powerful personal computers, large memories of available devices as well as graphic softwares and tools available with that devices and gadgets. Image acquisition, pre-processing, segmentation, representation, recognition and interpretation are the different basic steps through which image processing is carried out. [3][4].

IJCST Eighth Sense Research Group

ABSTRACT Ceramic tile is largely used in construction of floor at home, offices and shops and many other places. The image processing is playing an important role for find defect from the ceramic tile and industry maintaining the demand of market. In this paper we study classification of corner defect of square ceramic tile. Each corner follows the Pythagorean Theorem. Keywords:- Air Traffic Control, Global Information System

Ceramic tile is largely used in construction of floor at home, offices and shops and many other places. The image processing is playing an important role for find defect from the ceramic tile and industry maintaining the demand of market. In this paper we study classification of corner defect of square ceramic tile. Each corner follows the Pythagorean Theorem.

Ravindra Singh Rathore , Dr. Yogesh K U M A R Sharma

Abstract Objectives: To design an automated advanced grading system for maintaining quality assurance of ceramic tiles. Methods/ Statistical Analysis: We designed a machine that name is Upgraded Automated High Quality Maintaining Machine (UAHQMM). Customers required effect less and quality ceramic tiles. Findings: The block diagram of this research work presented three phases for automated quality Maintaining machine to maintain quality in ceramic tile industry. Application/Improvements: This automated machine is very useful for corner defect detection from different shapes of ceramic tile. In this research we discussed two shapes square and rectangle shapes. This modeled machine is very helpful for increasing production rate.

Ganesh Madhikar

Bulletin of Electrical Engineering and Informatics

Augustine O. Nwajana, PhD, FHEA, SMIEEE

Owing to recent technological advancement, computers and other devices running several image editing applications can be further exploited for digital image processing operations. This paper evaluates various image processing techniques using matrix laboratory (MATLAB-based analytics). Compared to the conventional techniques, MATLAB gives several advantages for image processing. MATLAB-based technique provides easy debugging with extensive data analysis and visualization, easy implementation and algorithmic-testing without recompilation. Besides, MATLAB's computational codes can be enhanced and exploited to process and create simulations of both still and video images. Moreover, MATLAB codes are much concise compared to c++, thus making it easier for perusing and troubleshooting. MATLAB can handle errors prior to execution by proposing various ways to make the codes faster. The proposed technique enables advanced image processing operations such as image cropping/resizing, image denoising, blur removal, and image sharpening. The study aims at providing readers with the most recent MATLAB-based image processing application-tools. We also provide an empirical-based method using two-dimensional discrete cosine transform (2D-DCT) derived from its coefficients. Using the most recent algorithms running on MATLAB toolbox, we performed simulations to evaluate the performance of our proposed technique. The results largely present MATLAB as a veritable approach for image processing operations.

Nirmala guptha

Green Revolution was introduced in agriculture to meet the food scarcity. Despite the increase of agricultural production, farmers are challenged by infestations. Infestation reduced the crop yield. Traditional method involved manual inspection of plants to identify diseases. With advancement in technology, the infested plant leaves can be captured into images and subjected to processing by computing element. The computing system are being trained to process the image using Machine Learning algorithms to classify the images. Processing the image and detecting with improved accuracy is essential. Random Forest classifier is used to detect the disease in Apple Leaf. The accuracy of prediction by Random Forest can be influenced by configuring its parameters. This Paper talks about the various options that can be applied to optimize Random Forest classifier for improving the accuracy of detecting Apple Leaf disease. Keywords— Machine Learning Algorithm, Random Forest, Apple leaf disease...

Prof. Hena Vadi , Pooja Vasani

— Cancer is one of the major diseases which cause death of human without any accident. It can be removed in early stage if it is detected. Earlier expert and specialized doctor examines Symptoms of cancer and do manually diagnosis. They visually examine medical images for any symptoms or signs of cancer in body. But manually detection of cancer is very time consuming. It is hard to detect cancer. Because of large amount of images, it is very harder and increase more manual work in diagnosis process, it increases laboratory work. For accurate diagnosis, very experienced or good trained Experts are required. Expert uses this technique but, accuracy is estimated about 70 to 75 percent. To improve speed and accuracy, computer aided system is best option. So computer aided system makes detection fast and accurate using image processing, pattern recognition and artificial intelligence. This paper reviews different computer aided techniques using image processing for cancer detection and diagnosis. This paper review focused on different segmentation techniques which are used to detect most common types of cancers like breast cancer, lung cancer, Bone Cancer and Brain cancerous Tumor. A proposed cancer detection and diagnosis framework inspired to make more research on image based computer aided system and develop more image based techniques for cancer diagnosis and detection.

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• 1. IMAGE PROCESSING ABSTRACT The ultimate aim in a large number of image processing applications is to extract important features from image data, from which a description, interpretation, or understanding of the scene can be provided by the machine. Image processing can be defined as, the processing or altering an existing image in a desired manner. This system allows the user to take hard copy of the image using printer routines and allows the user to store screen image into the disk file using file format (bmp, jpg, gif). Image processing in its general form pertains to the alteration and analysis of pictorial information. We find instances of image processing occurring all the time in our daily lives. Probably the most powerful image processing system is the human brain together with the eye. The system receives, enhances and stores images at enormous rates of speed. The objective of image processing is to visually enhance or statistically evaluate some aspect of an image not readily apparent in its original form. The basic principle of image processing operations carried out will assist us in greater perception and vision but does not add any information content. This objective is carried out through development and implementation of processing means necessary to operate upon images. The recent availability of sophisticated semi conductor digital devices and compact powerful computers, coupled with advances in image processing algorithms, has brought digital image processing to the fore front. Digital image processing has a broad spectrum and applications, such as remote sensing via satellites and other spacecraft image transmission and storage for business applications, medical processing, radar sonar and acoustic image processing, robotics and automated inspection of industrial parts. There are various features provided by system to edit an existing image, which are as follows Image scaling includes zooming and shrinking images. We can use enlarging to zoom in on the art of an image for closer examination. Image shrinking is useful for saving disk space, fitting a large image into smaller display and pasting several images into one image of the same size.
• 2. Image compression tool is an application, which works with BMP (bit map pattern File Format) gray scale images. The user will send images and according to the specification they will be modified. Image rotation tool is used to rotate the image by the specified angle. Resembling is used to increase the size of each pixel by a certain factor. We have used various filtering techniques like lightening, darkening, embossing, sharpening, softening etc. Edges characterize object boundaries and are therefore useful for segmentation, registration, and identification. Our system allows the user to detect the edges in a given image. We have developed a program, which can be used on compressed/uncompressed BMP, JPG, and GIF file formats to perform any of the above-mentioned functions. Existing System: There are applications is to extract important features from image data, from which a description, interpretation, or understanding of the scene can be provided by Machine. But there is no proper processing can be defined as, the processing or altering an existing image in a desired manner. Proposed System: The powerful image processing system is the human brain together with the eye. The system receives, enhances and stores images at enormous rates of speed. Image compression tool is an application, which works with BMP (bit map pattern File Format) gray scale images. The user will send images and according to the specification they will be modified. Image rotation tool is used to rotate the image by the specified angle. Resembling is used to increase the size of each pixel by a certain factor
• 3. Modules: Administrator: Admin is the authorized person to maintain Image Processing application.He can add uses of this application and can update and delete the users. User Module: User can load the images to be processed and can add the special effects and many other features to the existing application . File Module: In this module the files can be created, opened and loaded. A file can be selected to process the image .The files are of type image. Effects Module: Image can be blurred, sharpen , brightness can be increased and decreased. Image can be displayed in negative grayscale , Embossed and Engraved etc. Extras Module: In Extras module image height , width , measurements (inches and decimals ) can be changed .Image can be zoomed in and out. Mirror image can be displayed image can be flipped horizontally and vertically. NECESSITY OF IMAGE PROCESSING: Even though human beings are adept at interpreting images there are certain thresholds beyond which we cannot detect just-noticeable differences in the imagery. For example an analyst can detect only 8 to 16 shades of gray, even when data is recorded with 256 shades of gray. Hence , one may not be able to interpret data in the remaining shades of gray. Also it is necessary to continuously track large amounts of data and its storage is also a problem. To avoid all these difficulties one shall prefer processing of images by digital computers, which processes at a much faster rate than human beings do.
• 4. APPLICATIONS OF IMAGE PROCESSING: Applications of image processing include several fields such as 1. Remote sensing 2. Pictorial database 3. Radiology 4. Graphics design 5. High energy physics 6. Photo editing 7. Character recognition 8. Finger print matching 9. Cytology 10. Defense applications 11. Metallurgy SYSTEM REQUIREMENTS Hardware Requirements  Hard disk: - 80GB  RAM: - 512MB  Processor: - P V  Multimedia Key Board Software Requirements  Operating Systems: WINDOWS NT 4 / 2000 / XP  Technologies Used: Java,SWING, jdbc, jsp  Application Server: Apache Tomcat  Front End: html,jsp  Back End: Oracle 9.ior Access

Research on Image Processing Methods and Deep Learning Models in Structural Exterior Inspection

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Digital Photoelasticity pp 67–105 Cite as

• Digital Image Processing
• K. Ramesh 2  

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The term digital image processing (DIP) generally refers to the processing of a two-dimensional picture by a digital computer. A digital image is an array of real numbers represented by a finite number of bits. An image given in the form of a photograph or a slide is first digitised and stored as a matrix of binary digits in computer memory. This digitised image can then be processed and/or displayed on a high-resolution monitor. Early systems of image processing were configured around big computers such as a PDP 11 system. Recent advances in computer technology have brought in the development of plug-in cards, which can make a conventional PC into an image processing station. These cards are known as frame grabbers. Monochrome and colour frame grabbers are available in the market.

• Phase Lock Loop
• Frame Grabber
• Inverse Gamma

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Gonzalez RC, Woods RE (1993) Digital image processing. Addison-Wesley Publishing company, California

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Boyle WS, Smith GE (1970) Charge coupled semiconductor devices. Tech J Bell Systems 49:587–593

Ulicheny RA (1988) Dithering with Blue Noise. Proceedings of the IEEE 76(1): 56–79

CrossRef   Google Scholar  

Morrin TH (1974) A black & white representation of a grey scale picture. IEEE Trans - Computers 23:184–186

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Holst GC (1996) CCD arrays, cameras and displays. SPIE Optical Engineering Press, Bellingham Washington

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Department of Mechanical Engineering, Indian Institute of Technology, 208016, Kanpur, India

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© 2000 Springer-Verlag Berlin Heidelberg

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Ramesh, K. (2000). Digital Image Processing. In: Ramesh, K. (eds) Digital Photoelasticity. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59723-7_3

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DOI : https://doi.org/10.1007/978-3-642-59723-7_3

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