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Articoli di riviste sul tema "Image processing Digital techniques"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 1 agosto 2024

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1

Kumar Saini, Mukesh, Arun Saini, and Sachin Gupta. "Digital Image Processing Techniques for Leukemia Detection." International Journal of Science and Research (IJSR) 13, no. 6 (June 5, 2024): 1710–19. http://dx.doi.org/10.21275/sr24627090927.

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Maria Riasat. "Research on various image processing techniques." Open Access Research Journal of Chemistry and Pharmacy 1, no. 1 (December 30, 2021): 005–12. http://dx.doi.org/10.53022/oarjcp.2021.1.1.0029.

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Digital image processing deals with the manipulation of digital images through a digital computer. It is a subfield of signals and systems but focuses particularly on images. DIP focuses on developing a computer system that can perform processing on an image. The input of that system is a digital image and the system process that image using efficient algorithms and gives an image as an output. The most common example is Adobe Photoshop. It is one of the widely used applications for processing digital images. The image processing techniques play a vital role in image Acquisition, image pre-pro

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Raghavendra, V., N. Vinay kumar, and Manish Kumar. "Latest advancement in image processing techniques." International Journal of Engineering & Technology 7, no. 2.12 (April 3, 2018): 390. http://dx.doi.org/10.14419/ijet.v7i2.12.11357.

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Image processing is method of performing some operations on an image, for enhancing the image or for getting some information from that image, or for some other applications is nothing but Image Processing [1]. Image processing is one sort of signal processing, where input is an image and output may be an image, characteristics of that image or some features that image [1]. Image will be taken as a two dimensional signal and signal processing techniques will be applied to that two dimensional image. Image processing is one of the growing technologies [1]. In many real time applications image p

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Sweeta, J. Anto Germin, and Dr Sivagami B. "Contemporary Techniques in Digital Image Processing." International Journal of Computer Science and Engineering 6, no. 11 (November 25, 2019): 3–46. http://dx.doi.org/10.14445/23488387/ijcse-v6i11p109.

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Pradhan, Manini Monalisa. "Elimination Noise from Image Using Machine Learning Techniques." Oct-Nov 2023, no. 36 (October 20, 2023): 27–36. http://dx.doi.org/10.55529/jipirs.36.27.36.

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The Image Processing system is mostly used because of their easy accessibility of powerful personal computers, bulk memory machines with graphics software and others visual application. Of “Image Processing” is applied in a number of applications. These include in area of Remote Sensing in GIS application, Medical Imaging Processing for patient care application, Forensic Studies, Textiles engineering and design, Material science, Military Research, Film industry application, and Document processing, Graphic arts. An image is defined as an array, or a matrix, square pixel arranged in rows and c

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Mohanty, Sumant Sekhar, and Sushreeta Tripathy. "Application of Different Filtering Techniques in Digital Image Processing." Journal of Physics: Conference Series 2062, no. 1 (November 1, 2021): 012007. http://dx.doi.org/10.1088/1742-6596/2062/1/012007.

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Abstract Noise in an image is a random variation of brightness or color information in the original image. Noise is consistently presented in digital images during picture obtaining, coding, transmission, and processing steps. Image noise is most apparent in image regions with a low signal level. There are various reasons for the creation of noise in an image, such as electronic noise in amplifiers or detectors, disturbances and overheating of the sensor, disturbances in the medium of traveling for a digital image, etc. Noise is exceptionally hard to eliminate from the digital pictures without

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Iqbal, Saima, Wilayat Khan, Abdulrahman Alothaim, Aamir Qamar, Adi Alhudhaif, and Shtwai Alsubai. "Proving Reliability of Image Processing Techniques in Digital Forensics Applications." Security and Communication Networks 2022 (March 31, 2022): 1–17. http://dx.doi.org/10.1155/2022/1322264.

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Binary images have found its place in many applications, such as digital forensics involving legal documents, authentication of images, digital books, contracts, and text recognition. Modern digital forensics applications involve binary image processing as part of data hiding techniques for ownership protection, copyright control, and authentication of digital media. Whether in image forensics, health, or other fields, such transformations are often implemented in high-level languages without formal foundations. The lack of formal foundation questions the reliability of the image processing te

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Durai Anand Thangarajan and Sivasangari Rajeswaran. "Bacteria identification using digital image processing." International Journal of Science and Research Archive 12, no. 2 (July 30, 2024): 818–20. http://dx.doi.org/10.30574/ijsra.2024.12.2.1268.

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The identification of bacteria is an important and unavoidable task in medical disciplines and nutritional hygiene. But in the field of microbiology, No direct method is available for determination of bacterial species. The common manual technique is the microscopic sample analysis combined with more than 20 biochemical tests to identify the bacterium. These tests are more time consuming processes and required the training person for conducting these tests. To overcome the above problems the digital image processing can be used. The primary objective of the proposed work is to use the digital

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A, Suguna, Dinesh B V, Nithin S C, and Adarsh N S. "Image Processing." International Journal of Innovative Research in Information Security 09, no. 03 (June 23, 2023): 79–83. http://dx.doi.org/10.26562/ijiris.2023.v0903.06.

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Image processing entails altering an image's composition to enhance its graphical content for human interpretation and autonomous machine perception. Digital image processing is a subset of the electronic domain in which an image is transformed into a collection of tin y numbers, or pixels, that reflect a physical property, like s cene radiance, are stored in a digital memory, and are then processed by a computer or other digital hardware. Two key application areas have sparked interest in digital i mage processing techniques: improving pictorial information for human interpretation and proces

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P., Himali, Hardik Modi, Manoj Pandya, and M. B. Potdar. "Leukemia Detection using Digital Image Processing Techniques." International Journal of Applied Information Systems 10, no. 1 (November 4, 2015): 43–51. http://dx.doi.org/10.5120/ijais2015451461.

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Kumar, Arvind, and Ashutosh Sharma. "Multiresolution Transform Techniques in Digital Image Processing." International Journal of Computer Applications 123, no. 12 (August 18, 2015): 44–49. http://dx.doi.org/10.5120/ijca2015905530.

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McKenna, S. P., and W. R. McGillis. "Performance of digital image velocimetry processing techniques." Experiments in Fluids 32, no. 1 (January 1, 2002): 106–15. http://dx.doi.org/10.1007/s003480200011.

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Döler, W., N. Steinhöfel, and A. Jäger. "Digital image processing techniques for cephalometric analysis." Computers in Biology and Medicine 21, no. 1-2 (January 1991): 23–33. http://dx.doi.org/10.1016/0010-4825(91)90032-5.

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Patel, Jagrti, Meghna Jain, and Papiya Dutta. "Detection of Faults Using Digital Image Processing Technique." Asian Journal of Engineering and Applied Technology 2, no. 1 (May 5, 2013): 36–39. http://dx.doi.org/10.51983/ajeat-2013.2.1.644.

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This paper presents an approach to automatic detection of fabric defects using digital image processing. In Textile industry automatic fabric inspection is important to maintain the quality of fabric. Fabric defect detection is carried out manually with human visual inspection for a long time. This paper proposes an approach to recognize fabric defects in textile industry for minimizing production cost and time. Fabric analysis is performed on the basis of digital images of the fabric. The recognizer acquires digital fabric images by image acquisition device and converts that image into binary

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Tanwar, Himanshu, and Gaurav Kumar. "Review Paper on Techniques of 2D to 3D Image Reconstruction." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (October 31, 2023): 370–74. http://dx.doi.org/10.22214/ijraset.2023.55996.

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Abstract: The review paper emphasize on reducing technologies for 2D and 3D imaging, as well as model conversion. Although the popularity of 3D hardware is growing rapidly in the present era, 3D content is still dominated by its 2D counterpart. There are two main categories of image processing now available in the market, namely analogue and digital image processing. To produce hard copies such as scanned pictures and printouts, with images being the most common output, the analogue IP technique is used. On the other hand, Digital IP is used to manipulate digital images using computers, the ou

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Mishra, Harshita, and Anuradha Misra. "Techniques for Image Segmentation: A Critical Review." International Journal of Research in Advent Technology 9, no. 3 (April 10, 2021): 1–4. http://dx.doi.org/10.32622/ijrat.93202101.

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In today’s world there is requirement of some techniques or methods that will be helpful for retrieval of the information from the images. Information those are important for finding solution to the problems in the present time are needed. In this review we will study the processing involved in the digitalization of the image. The set or proper array of the pixels that is also called as picture element is known as image. The positioning of these pixels is in matrix which is formed in columns and rows. The image undergoes the process of digitalization by which a digital image is formed. This pr

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T, Nayana, and Dr T. D. Shashikala. "CLASSIFICATION OF ARECANUT USING DIGITAL IMAGE PROCESSING." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 09 (September 1, 2023): 1–11. http://dx.doi.org/10.55041/ijsrem25828.

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In agricultural domain research, image processing and machine learning techniques play an important role. One of India’s major cash crops is arecanut. A significant challenge in the field of agriculture is the grouping of arecanut. Arecanut categorization using image processing is an emerging field of research that aims to automate the process of grouping arecanut based on its color and shape using digital images. This paper presents a classification of Arecanut using Convolutional Neural Networks. General Terms Image Processing, Classification Keywords Arecanut classification, Machine learnin

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Li, Yiyang. "Digital signal processing techniques for image enhancement and restoration." Applied and Computational Engineering 17, no. 1 (October 23, 2023): 198–205. http://dx.doi.org/10.54254/2755-2721/17/20230940.

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Digital image processing has become a fundamental tool in modern image processing, including image enhancement and restoration. This paper reviews important image enhancement and restoration techniques in digital image processing. First, some important image enhancement techniques such as histogram equalization are introduced and compared in detail, including their advantages, disadvantages, and application scenarios. Secondly, for image restoration techniques, this paper introduces deblurring techniques such as deconvolution and blind deconvolution, explaining their working principles and app

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S, Agnes Shifani, Akshaya D, Kaviya M, and Kiruthiga K. "A Comprehensive Survey on Crack detection of Bone using various techniques." Bulletin of Scientific Research 2, no. 2 (August 19, 2020): 1–7. http://dx.doi.org/10.34256/bsr2021.

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Digital image processing plays a key role in manipulation of image and extracting the maximum amount of data from image with help of various algorithm. Digital image correlation algorithm determines the displacement and deformation of pattern across several images. Creating innovation are developing every day in various fields, particularly in restoration condition. Notwithstanding, still some old strategies are very famous. X-ray or CT images are one among the system for identification of bone cracks. during this article, we offer a comprehensive overview of various algorithm and techniques o

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Yahya, Ali Abdullah. "Teaching Digital Image Processing Topics via Matlab Techniques." International Journal of Information and Education Technology 9, no. 10 (2019): 729–34. http://dx.doi.org/10.18178/ijiet.2019.9.10.1294.

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Wen, Che-Yen, and Chiu-Chung Yu. "Fingerprint Pattern Restoration by Digital Image Processing Techniques." Journal of Forensic Sciences 48, no. 5 (September 1, 2003): 2002385. http://dx.doi.org/10.1520/jfs2002385.

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Vorozhtsov, E. V. "On shock localization by digital image processing techniques." Computers & Fluids 15, no. 1 (January 1987): 13–45. http://dx.doi.org/10.1016/0045-7930(87)90003-x.

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Liao, Qinzhuo, Shaohua You, Maolei Cui, Xiaoxi Guo, Murtada Saleh Aljawad, and Shirish Patil. "Digital Core Permeability Computation by Image Processing Techniques." Water 15, no. 11 (May 24, 2023): 1995. http://dx.doi.org/10.3390/w15111995.

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Calculation of REV (representative elementary volume) properties of geological porous media refers to the process of creating a 3D digital representation of a rock sample, typically obtained from imaging techniques such as X-ray microtomography. This technique allows for a detailed analysis of the internal structure and the properties of rocks, as well as precise calculation of various flow parameters. However, one major challenge with calculation of REV properties of geological porous media is the high computational cost required to generate accurate results, especially for large and complex

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Kaur, Amanpreet. "Colour Image Segmentation using Background Subtraction with Global and Local Threshold." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 20, 2021): 1652–57. http://dx.doi.org/10.22214/ijraset.2021.35340.

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Image segmentation is one of the fundamental and essential steps in all the major applications of digital image processing. In this process the digital image is divided into various regions which are also known as segments. These segmented parts of the digital image could be used for further processing like detection of types of objects present in the segmented region, various tumors present in the digital images or the scene understanding process. Usually segmentation is classified as local segmentation and the global segmentation. Image segmentation is also classified on the basis of digital

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Ahmed, Awa, and Osman Sharif. "Image Processing Techniques-based fire detection." Sulaimani Journal for Engineering Sciences 8, no. 1 (August 1, 2021): 23–34. http://dx.doi.org/10.17656/sjes.10145.

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In this paper different fire detection systems and techniques has been reviewed, many techniques have been developed for the purpose of early fire detection in different scenarios. The most accurate technique used among all these methods is Image Processing based Techniques. Different color models like RGB, HSI, CIE L*a*b and YCbCr have been used along with different edge detection algorithms like Sobel and Novel edge detection, finally the color segmentation technique was discussed in the review paper. All the mentioned methods in these papers have significantly proved to detect fire and flam

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Tang, Jinyu. "An Optimized Digital Image Processing Algorithm for Digital Oil Painting." Mobile Information Systems 2022 (May 31, 2022): 1–10. http://dx.doi.org/10.1155/2022/4956839.

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Human civilization’s accomplishments have grown with the passage of time and the advancement of society. With the fast growth of computer networks and information technology, the conventional method of information transmission based on words cannot fulfill the demands of people in the current era. As a result, in this age of extensive information and image processing techniques, images as a means of information sharing are becoming increasingly popular. As we know, digital image processing knowledge has a far-reaching impact in the field of artistic creation, among which the creation of oil pa

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Lee, Jong Jae, Masanobu Shinozuka, and Soo Jin Cho. "Remote Sensing of Bridge Displacement Using Digital Image Processing Techniques." Key Engineering Materials 321-323 (October 2006): 404–9. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.404.

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In this study, an optical method of real-time displacement measurement of such bridges was carried out by means of digital image processing techniques. A commercially available digital video camera combined with a telescopic device takes a motion picture of the target panel with known geometry, which is installed on the measurement location of a bridge. The displacement of the target is calculated based on the captured images in real-time manner using image processing techniques, which require a texture recognition algorithm, projection of the captured image, and calculation of the actual disp

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Wen, Cathlyn Y., and Robert J. Beaton. "Subjective Image Quality Evaluation of Image Compression Techniques." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 23 (October 1996): 1188–92. http://dx.doi.org/10.1177/154193129604002309.

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Image compression reduces the amount of data in digital images and, therefore, allows efficient storage, processing, and transmission of pictorial information. However, compression algorithms can degrade image quality by introducing artifacts, which may be unacceptable for users' tasks. This work examined the subjective effects of JPEG and wavelet compression algorithms on a series of medical images. Six digitized chest images were processed by each algorithm at various compression levels. Twelve radiologists rated the perceived image quality of the compressed images relative to the correspond

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Kavitha S Patil,. "Digital Image and Video Processing: Algorithms and Applications." Journal of Electrical Systems 20, no. 3s (April 4, 2024): 1390–96. http://dx.doi.org/10.52783/jes.1516.

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Many of the techniques that are used in digital image and video processing were developed in the 1960s at Bell Laboratories. These techniques have applications in a variety of fields, including medical imaging, videophone, character recognition, satellite imagery, and wire-photo standards conversion. Additional applications include enhancement of photographs or vidoes. The early stages of image and video processing were developed with the intention of enhancing the overall quality of the image or video. For the purpose of enhancing the visual effect of humans, it is intended for human beings.

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Alayat, Abdulsalam Basher, and Hend Ali Omar. "Pavement Surface Distress Detection Using Digital Image Processing Techniques." Jurnal Kejuruteraan 35, no. 1 (January 30, 2023): 247–56. http://dx.doi.org/10.17576/jkukm-2023-35(1)-24.

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Road safety and pavement condition are considered top priorities in our civilized societies, and it’s important that the pavement condition remains in an excellent state for a long time. However, eventually, the pavement will get exposed to different types of distresses as a result of traffic loads, rough environment conditions, soil conditions, and underline subgrade. Therefore, to achieve the required standards for the pavement surface roads in our country and provide the best performance: detection and measurements of distresses extension must be included in maintenance preparation. This pa

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K Ganapathi Babu, Sunil Kumar Dasari, and C Yosepu. "An Overview: Image Processing Techniques and Its Applications." international journal of engineering technology and management sciences 7, no. 3 (2023): 883–88. http://dx.doi.org/10.46647/ijetms.2023.v07i03.135.

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The use of digital image processing techniques has been widely flourished and they are now used for all kinds of tasks in various areas. Image processing helps in the identification of objects that are invisible, and different techniques makes it faster and cost effective. This paper gives you an overview on various digital image processing techniques and its applications like remote sensing, medical imaging, forensic studies etc.

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Peters, Klaus-Ruediger, and Eisaku Oho. "New digital image processing technology for FSEM microscopy." Proceedings, annual meeting, Electron Microscopy Society of America 51 (August 1, 1993): 212–13. http://dx.doi.org/10.1017/s0424820100146904.

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Digital image acquisition and processing can provide many advantages over conventional analog image information handling, i.e., undisturbed access to the “raw data set”, quantitative analysis of the image information, and reduced costs and increased flexibility of image data handling. However, it may principally change microscopy by providing a new facility for instant exhaustive data presentation in acquired images. Detail imaging is one of the basic microscopic tasks but visual access to detail information is cumbersome and often left to post-session data analysis. A dedicated software/hardw

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Hussin, R., M. Rizon Juhari, Ng Wei Kang, R. C. Ismail, and A. Kamarudin. "Digital Image Processing Techniques for Object Detection From Complex Background Image." Procedia Engineering 41 (2012): 340–44. http://dx.doi.org/10.1016/j.proeng.2012.07.182.

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Moon, Ki Hoon, Augusto Cannone Falchetto, and Jin Hoon Jeong. "Microstructural analysis of asphalt mixtures using digital image processing techniques." Canadian Journal of Civil Engineering 41, no. 1 (January 2014): 74–86. http://dx.doi.org/10.1139/cjce-2013-0250.

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In this paper, the internal microstructure of asphalt mixture is analyzed through digital image processing (DIP) of two-dimensional asphalt mixture images. A set of 12 mixtures prepared with two binders, two air voids percentages, and different recycled asphalt pavement (RAP) contents is used. First, small asphalt mixture beams of the same size of bending beam rheometer specimens are prepared for the images acquisition. Then, based on mixture volumetric properties, a three-phase material model is obtained. Finally, 2- and 3-point correlation functions of the material phases are numerically eva

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Cai, Han Ming, Pei Yao Wang, and Xiao Mei Song. "Detecting Thread Features Based on Digital Image Processing Techniques." Advanced Materials Research 889-890 (February 2014): 1107–10. http://dx.doi.org/10.4028/www.scientific.net/amr.889-890.1107.

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Thread features of the traditional measuring method mainly adopts working gauge measurement, due to limitations in the traditional thread features measurement accuracy is relatively low, the efficiency is low, the cost is high. The thread features detection method based on digital image processing techniques using CCD to obtain basic image of thread, processing the thread image, extracting thread outline, calculating thread features through the computer, improves the efficiency, saves the cost.

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Devane, Vighnesh, Ganesh Sahane, Hritish Khairmode, and Gaurav Datkhile. "Lane Detection Techniques using Image Processing." ITM Web of Conferences 40 (2021): 03011. http://dx.doi.org/10.1051/itmconf/20214003011.

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Lane detection is a developing technology that is implemented in vehicles to enable autonomous navigation. Most lane detection systems are designed for roads with proper structure relying on the existence of markings. The main shortcoming of these approaches is that they might give inaccurate results or not work at all in situations involving unclear markings or the absence of them. In this study one such approach for detecting lanes on an unmarked road is reviewed followed by an improved approach. Both the approaches are based on digital image processing techniques and purely work on vision o

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Mahankali, Sreenath, and Giridhar Valikala. "Comparison of Compressive Strength of M30 Grade Concrete with Destructive and Nondestructive Procedures Using Digital Image Processing as a Technique." Advances in Civil Engineering 2022 (June 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/4649660.

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Destructive, semidestructive, and nondestructive methods are used to assess the compressive strength of concrete and its substantial mechanical property. In the destructive method, samples of concrete are crushed and treated under compression to determine its compressive strength. As such, the impact is seen on test results like the method of casting and compaction. The tests on concrete become limited in the destructive method and are confined to predict compressive strength, flexural strength, etc. To overcome its limitations and to study concrete matrix, semidestructive and nondestructive t

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SANCHEZ, ANGEL, JOSE F. VELEZ, ANA BELEN MORENO, and JOSE L. ESTEBAN. "INTRODUCING ALGORITHM DESIGN TECHNIQUES IN UNDERGRADUATE DIGITAL IMAGE PROCESSING COURSES." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 05 (August 2001): 789–803. http://dx.doi.org/10.1142/s0218001401001155.

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This paper documents the development and first offering of an undergraduate course in Digital Image Processing at the Rey Juan Carlos University, Madrid (Spain). The paper describes how the appropriate introduction of main Algorithm Design Techniques can successfully assist the students to achieve a comprehensive understanding of image operations and related algorithms. Image processing problems offer a natural way to present real world problems where the students can use their algorithmic knowledge. Furthermore, image processing solutions are needed from a methodological development and requi

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Patil, Rajesh, and Surendra Bhosale. "Medical Image Denoising Techniques: A Review." International Journal on Engineering, Science and Technology 4, no. 1 (January 17, 2022): 21–33. http://dx.doi.org/10.46328/ijonest.76.

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Medical imaging means the methods and procedures used for creating pictures of various parts of the human body for numerous clinical objectives. These images are constantly gets dirtied by noise during picture acquisition and transmission, resulting in low quality images. Noise is the unwanted signal which corrupts the important and desirable information. The noises can be categorized into different types based on their nature and origin. e.g. Gaussian, the impulsive and speckle noise etc. The removal of noise is very necessary for proper analysis and diagnosis. Filtering noise helps to recrea

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Rodrigues, Pedro, Manuel João Ferreira, and João Luís Monteiro. "Quantum Computation Perspectives in Medical Image Processing." International Journal of Nanotechnology and Molecular Computation 2, no. 2 (April 2010): 16–46. http://dx.doi.org/10.4018/978-1-61520-670-4.ch006.

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The need to increase the complexity of computational methods to produce improvements in functional performance, particularly in medical image processing applications, leads to find suitable physical devices. This chapter describes two ways of adapting the techniques of image processing to quantum devices. This kind of computing can achieve, for some problems, unparalleled performance as compared to classic computing. In the first method, using the quantum Grover’s algorithm how to implement image processing techniques under quantum rules is shown. In the second method, using diffraction and in

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FUJIWARA, Tadao, Shuji NISHIHARA, and Koji HIROSE. "Digital image processing techniques for color flow-visualization photograph." JOURNAL OF THE FLOW VISUALIZATION SOCIETY OF JAPAN 8, no. 28 (1988): 32–38. http://dx.doi.org/10.3154/jvs1981.8.32.

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Prasad, Jayashree Rajesh. "Review of Advanced Image Processing Techniques: Digital Elevation Model." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 2733–37. http://dx.doi.org/10.22214/ijraset.2022.44422.

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Abstract: This paper gives an in depth insight into the current as well as the previous systems or techniques that have been used in order to perform advanced image processing. These systems or techniques have been implemented or tested in the areas of Germany, The United States of America, India, China, Indonesia and many more. The review aims to explore challenges and opportunities in the field computational and image processing areas of the industry.

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FUJIWARA, Tadao, Shuji NISHIHARA, and Koji HIROSE. "Color Flow-Visualization Photography and Digital Image Processing Techniques." JSME international journal. Ser. 2, Fluids engineering, heat transfer, power, combustion, thermophysical properties 31, no. 1 (1988): 39–46. http://dx.doi.org/10.1299/jsmeb1988.31.1_39.

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Ozkaya, Yasar A. "Digital image processing and illumination techniques for yarn characterization." Journal of Electronic Imaging 14, no. 2 (April 1, 2005): 023001. http://dx.doi.org/10.1117/1.1902743.

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FUJIWARA, Tadao, Shuji NISHIHARA, and Koji HIROSE. "Color flow-visualization photography and digital image processing techniques." Transactions of the Japan Society of Mechanical Engineers Series B 53, no. 493 (1987): 2762–70. http://dx.doi.org/10.1299/kikaib.53.2762.

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Bennamoun, M., and A. Bodnarova. "Digital Image Processing Techniques for Automatic Textile Quality Control." Systems Analysis Modelling Simulation 43, no. 11 (November 2003): 1581–614. http://dx.doi.org/10.1080/0232929032000115083.

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Kaur, Rajvinder, and Rupinder Kaur. "A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing." International Journal of Computer Applications 179, no. 45 (May 18, 2018): 24–27. http://dx.doi.org/10.5120/ijca2018917133.

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Gill, Jasmeen, Akshay Girdhar, and Tejwant Singh. "A Review of Enhancement and Segmentation Techniques for Digital Images." International Journal of Image and Graphics 19, no. 03 (July 2019): 1950013. http://dx.doi.org/10.1142/s021946781950013x.

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Image enhancement and segmentation are the two imperative steps while processing digital images. The goal of enhancement is to improve the quality of images so as to nullify the effect of poor illumination conditions during image acquisition. Afterwards, segmentation is performed to extract region of interest (ROI) from the background details of the image. There is a vast literature available for both the techniques. Therefore, this paper is intended to summarize the basic as well as advanced enhancement and segmentation techniques under a single heading; to provide an insight for future resea

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Putra, Edi, and Lina Lina. "KAJIAN TENTANG PERBAIKAN KUALITAS CITRA DALAM AIR MENGGUNAKAN METODE DARK CHANNEL PRIOR." Jurnal Ilmu Komputer dan Sistem Informasi 5, no. 1 (August 25, 2017): 13. http://dx.doi.org/10.24912/jiksi.v5i1.765.

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Digital image processing is a branch of engineering informatics. image processing is an attempt to change your photo or image into another by using certain techniques. The process of changing the image data into digital data by using a computer known as digital image processing. The purpose of this application is to improve the image quality of the water using test images and imagery training, to train image by image is in the water, while the test images by using the image processing Dark Channel Prior. The image that was in the sea water murky and foggy be processed and then do a comparison

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Saha, Tanusree, and Dr Kumar Vishal. "A Study of Application of Digital Image Processing in Medical Field and Medical Image Segmentation by Edge Detection." International Journal of Emerging Science and Engineering 12, no. 4 (May 30, 2024): 3–8. http://dx.doi.org/10.35940/ijese.g9890.12040324.

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There has been a lot of recent development in the domain of image processing and associated imaging techniques. Medical imaging is about the practice to capture images of different fragments of the body for diagnostic or investigative purposes. The number of imaging procedures performed each week is in the millions. This study presents the promising image processing methods currently in use in the medical field. The rapid expansion of medical imaging can be attributed to advancements in image processing methods, including image recognition, enhancement, and analysis. Utilised in the diagnosis

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