scholarly journals Detection And Restoration of Cracked Digitized Paintings and Manuscripts Using Image Processing

2018 ◽  
Vol 7 (2.34) ◽  
pp. 39
Author(s):  
Nawafil Abdulwahab Farajalla Ali ◽  
Imad Fakhri Taha Al-Shaikhli ◽  
Raini Hasan
Keyword(s):  
Image Processing ◽  
Median Filter ◽  
Computer Aided Analysis ◽  
Computer Aided ◽  
Drying Up ◽  
Weighted Median ◽  
Mechanical Factors ◽  
Region Growth

Ancient paintings are cultural heritage that can be preserved via computer aided analysis and processing. These paintings deteriorate due to undesired cracks, which are caused by aging, drying up of painting material, and mechanical factors. These heritages need to be restored to their respective original or near-original states. There are different techniques and methodologies that can be used to conserve and restore the overall quality of these images. The main objective of this study is to analyze techniques and methodologies that have been developed for the detection, classification of small patterns, and restoration of cracks in digitized old painting and manuscripts. The purpose of the developed algorithm is to identify cracks using the thresholding operation, which was the output of the top-hat transform morphology. Afterwards, the breaks, which were wrongly identified as cracks, were separated for utilization in a semi-automatic procedure based on region growth. Finally, both the median filter and weighted median techniques were applied to fill the cracks and enhance image quality. 

scholarly journals Detection and Restoration of Cracked Digitized Paintings and Manuscripts using Image Processing - A Survey

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Nawafil Abdulwahab Ali ◽  
Imad Fakhri Taha Al Shaikhli
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Original State ◽  
Drying Up ◽  
Processing Techniques

Abstract— The restoration of paintings and manuscripts is defined as the process of restoring old and damaged artworks and documents exhibiting cracks. Cracks are caused by three factors; aging, drying up of painting material, and mechanical. It is necessary that cultural heritages be restored to their original or a near-original state. To enhance the overall quality of the image, there are different techniques and methodologies that can be used for conservation and restoration. The main objective of this study is to analyse techniques and methodologies that have been developed for the detection, classification of small patterns, and restoration of cracks in digitized old painting and manuscripts. The purpose of this research is to present previous works on detection and restoration of cracks using image processing techniques and methodologies.

scholarly journals Wavelet-Based Weighted Median Filter For Image Denoising Of MRI Brain Images

2018 ◽  
Vol 10 (1) ◽  
pp. 201 ◽  
Author(s):  
N. Rajalakshmi ◽  
K. Narayanan ◽  
P. Amudhavalli
Keyword(s):  
Additive White Gaussian Noise ◽  
Median Filter ◽  
Wiener Filter ◽  
Brain Images ◽  
Visual Appearance ◽  
Mri Brain ◽  
Weighted Median ◽  
Weighted Median Filter ◽  
Mri Brain Images

<p>Preliminary diagnosing of MRI images from the hospital cannot be relied on because of the chances of occurrence of artifacts resulting in degraded quality of image, while others may be confused with pathology. Obtained MRI image usually contains limited artifacts. It becomes complex one for doctors in analyzing them. By increasing the contrast of an image, it will be easy to analyze. In order to find the tumor part efficiently MRI brain image should be enhanced properly. The image enhancement methods mainly improve the visual appearance of MRI images. The goal of denoising is to remove the noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. In this paper effectiveness of seven denoising algorithms viz. median filter, wiener filter, wavelet filter, wavelet based wiener, NLM, wavelet based NLM, proposed wavelet based weighted median filter(WMF) using MRI images in the presence of additive white Gaussian noise is compared. The experimental results are analyzed in terms of various image quality metrics.</p>

scholarly journals Implementasi Metode Super Resolusi Untuk Meningkatkan Kualitas Citra Hasil Screenshot

2020 ◽  
Vol 7 (3) ◽  
pp. 432
Author(s):  
Windi Astuti
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Super Resolution ◽  
Linear Interpolation ◽  
Resolution Method ◽  
Image Zooming ◽  
Image Enlargement ◽  
Three Stages

Various types of image processing that can be done by computers, such as improving image quality is one of the fields that is quite popular until now. Improving the quality of an image is necessary so that someone can observe the image clearly and in detail without any disturbance. An image can experience major disturbances or errors in an image such as the image of the screenshot is used as a sample. The results of the image from the screenshot have the smallest sharpness and smoothness of the image, so to get a better image is usually done enlargement of the image. After the screenshot results are obtained then, the next process is cropping the image and the image looks like there are disturbances such as visible blur and cracked. To get an enlarged image (Zooming image) by adding new pixels or points. This is done by the super resolution method, super resolution has three stages of completion, first Registration, Interpolation, and Reconstruction. For magnification done by linear interpolation and reconstruction using a median filter for image refinement. This method is expected to be able to solve the problem of improving image quality in image enlargement applications. This study discusses that the process carried out to implement image enlargement based on the super resolution method is then built by using R2013a matlab as an editor to edit programs

scholarly journals Detection of Avian Pox Disease using K-Means and Svm Classifer

2019 ◽  
Vol 8 (9) ◽  
pp. 3238-3241
Keyword(s):  
Image Processing ◽  
Impulse Noise ◽  
Performance Test ◽  
Digital Images ◽  
Median Filter ◽  
Performance Tests ◽  
Crucial Step ◽  
Avian Pox ◽  
And Performance

This paper discusses about various methods involved in detection of avian pox in the birds using images. Digital images are corrupted while sending and receiving the images because of noisy sensors which degrade the quality of image. Pre-processing becomes an initial and crucial step in image processing to remove the noise and maintain fine details and texture of the image. Pre-processed images can be used for further work. Mean, Median, Weiner, Mean Maximum, Mean Minimum filters are used and performance tests are made using Signal Noise Ratio. Based on the performance test, removal of impulse noise is well done by Median filter and produces the best result when compared to other filters. K-Means clustering and SVM are used for identification of the disease.

scholarly journals Computational Efficient Method for Denoising of Salt and Pepper Noise for Image Enhancement

2020 ◽  
Vol 8 (6) ◽  
pp. 538-543
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Noise Removal ◽  
Input Image ◽  
Filter Method ◽  
Pixel Intensity ◽  
Feature Information ◽  
Salt And Pepper

Digital Image processing is basically a computer-algorithm which is used to enhance the quality of image to understand the feature of image and exact the meaningful features information from image. Image processing has wider range of algorithms to be applied to the input image and can escape the difficulty as the signal distortion and add noise in input image at the time of processing of images. Noises affect the image visualization and degraded the image quality, sometimes chaotic variation in value of pixel intensity, lighting effect or because of poor contrast, image can’t be used directly because many time interest feature information not received as output that’s one reason image processing is significant for removal of noise from images, so noise removal is becomes trending field in image processing. Median filter method is one of most popular method to eradicate the effect of noise from image and it enhances the image quality to take meaningful feature easily from image. In this paper removing of noise using median filter to enhance the image quality is discussed, also the importance and applications of enhancement technique are covered. Parameter PSNR and MSE is also used to analysis the image quality along with the visualization of image. Simulation results show that Median filter gives good outcome for salt & pepper noise as compare to other filtering method. MATLAB software is used as simulation tool.

scholarly journals CONSTANT TIME SCANNING AND BETTER EDGE PRESERVATION FOR BETTER PERFORMING AND QUALITY OF MEDIAN FILTER

2012 ◽  
pp. 114-116
Author(s):  
RITWIK SHARMA ◽  
SHUBHAM HARNAL
Keyword(s):  
Image Processing ◽  
Median Filter ◽  
Median Filtering ◽  
Edge Preservation ◽  
Median Filters ◽  
Novel Approach ◽  
Time Scanning ◽  
The Cost ◽  
Salt And Pepper

The median filter is an important filter in many image processing algorithms and especially in removal of salt and pepper noise. Traditional median filters either focus on improving the performance or the quality of the median filtering. Generally, the methods which optimize performance do so at the cost of quality and vice-versa. In this paper a novel approach to median filtering is presented providing both better performance and quality without sacrificing either. The analysis is presented with respect to image processing and the results obtained are presented in tabular form.

scholarly journals Design of Exponentially Weighted Median Filter Cascaded With Adaptive Median Filter

2021 ◽  
Vol 2089 (1) ◽  
pp. 012020
Author(s):  
Praveen Kumar Nalli ◽  
Kalyan Sagar Kadali ◽  
Ramu Bhukya ◽  
Y.T.R. Palleswari ◽  
Asapu Siva ◽  
...  
Keyword(s):  
Median Filter ◽  
Second Phase ◽  
Median Filters ◽  
Fixed Weight ◽  
Adaptive Median Filter ◽  
Weighted Median ◽  
Weighted Median Filters ◽  
Cascaded Filter ◽  
Weighted Median Filter

Abstract The objective of this paper is to design an II phase algorithm employing median filters for enlightening the performance in removing impulse noise during the processing of the image. The cascaded filter section employs an Adaptive median filter in the first phase followed by a Recursive weighted median filter (RWM) in the second phase. The RWM filter weight is selected with the Median Controlled Algorithm. As a design parameter, the exponential weights of RWM filters are used in the feedback path. The projected algorithm can achieve suggestively improved quality of image when compared to fixed weight or the Center Weighted Median filters.

scholarly journals An Automated Detection and Classification of Cataract and Glaucoma Using RCNN

2021 ◽  
Vol 9 (VI) ◽  
pp. 4959-4967
Author(s):  
Alida E T
Keyword(s):  
Neural Network ◽  
Early Detection ◽  
Automated Detection ◽  
Classification Approach ◽  
Glaucoma Screening ◽  
Glaucoma Detection ◽  
Computer Aided Analysis ◽  
The World ◽  
Computer Aided

one of the human’s deterioration is visual impairment. Cataract and Glaucoma are the most prevailing cause blindness in the world. Early detection and treatment is the best way to prevent the blindness. Currently grading is done by human graders, it is found to be time taking and grading is usually subjective. Computer aided analysis can help human graders. An automated cataract and glaucoma detection and classification approach is proposed in this paper, to grade more objectively. Region based convolution neural network (RCNN) is used to classification process. The percentage of accuracy of classification obtained for cataract and glaucoma is 98.9% and 97.8% respectively. The method is especially suitable for cataract and glaucoma screening in the underdeveloped areas or areas which are in shortage of ophthalmic resources. It can also improve the accessibility of ophthalmic medical treatment.

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