A Digital Watermarking Algorithm Based on the Wavelet Bit Plane Coding

2013 ◽  
Vol 821-822 ◽  
pp. 1438-1441
Author(s):  
Gao Yan ◽  
Yan Liang ◽  
Xin Zhou ◽  
Chun Xia Qi
Keyword(s):  
Image Processing ◽  
Digital Watermarking ◽  
Original Image ◽  
A Algorithm ◽  
Bit Plane Coding ◽  
Bit Plane ◽  
The Difference ◽  
Bit Planes ◽  
Processing Techniques ◽  
Signal Processing Techniques

In this paper a algorithm of digital image watermark based on wavelet bit plane is introduced, and the original image is not required for detecting the watermarking. The digital watermark is embedded by changing information of some bit planes in DWT images at different resolutions. The watermark can be extracted on the difference bit plane values of subimages of the decomposed watermarked image which is then mapped to an image with a few shades of gray. Experimental results show that the watermark is robust to several signal processing techniques, including JPEG compression and some image processing operations

A DCT-Domain System for Digital Watermarking

2013 ◽  
Vol 321-324 ◽  
pp. 2609-2612
Author(s):  
Yan Liang ◽  
Gao Yan ◽  
Chun Xia Qi
Keyword(s):  
Signal Processing ◽  
Digital Watermarking ◽  
Copyright Protection ◽  
Random Sequence ◽  
Multimedia Data ◽  
Dct Domain ◽  
Digital Document ◽  
Dct Coefficients ◽  
Processing Techniques ◽  
Signal Processing Techniques

Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data in a networked environment. It makes possible to tightly associated to a digital document a code allowing the identification of the data creator, owner, authorized consumer, and so on. In this paper a new DCT-domain system for digital watermarking algorithm for digital images is presented: the method, which operates in the frequency domain, embeds a pseudo-random sequence of scrambled image in a selected set of DCT coefficients. After embedding, the watermark is adapted to the image by exploiting the masking characteristics of the human visual system, thus ensuring the watermark invisibility. By exploiting the statistical properties of the embedded sequence, the mark can be reliably extracted without resorting to the original uncorrupted image. Experimental results demonstrate that the watermark is robust to several signal processing techniques, including JPEG compression, cut, fuzzy, addition of noise, and sharpen.

scholarly journals Enhancement of Satellite Imagesusing Image Sharpening Technique

2019 ◽  
Vol 8 (6S2) ◽  
pp. 351-354
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Histogram Equalization ◽  
Grayscale Image ◽  
Original Image ◽  
High Quality ◽  
Wide Range ◽  
Equalization Technique ◽  
The Difference

In many image processing applications, a wide range of image enhancement techniques are being proposed. Many of these techniques demanda lot of critical and advance steps, but the resultingimage perception is not satisfactory. This paper proposes a novel sharpening method which is being experimented with additional steps. In the first step, the color image is transformed into grayscale image, then edge detection process is applied using Laplacian technique. Then deduct this image from the original image. The resulting image is as expected; After performing the enhancement process,the high quality of the image can be indicated using the Tenengrad criterion. The resulting image manifested the difference in certain areas, the dimension and the depth as well. Histogram equalization technique can also be applied to change the images color.

scholarly journals Estimation accuracy of covariance matrices when their eigenvalues are almost duplicated

2018 ◽  
Vol 7 ◽  
Author(s):  
Kantaro Shimomura ◽  
Kazushi Ikeda
Keyword(s):  
Covariance Matrix ◽  
Estimation Method ◽  
Estimation Accuracy ◽  
Essential Information ◽  
The Matrix ◽  
The Difference ◽  
Processing Techniques ◽  
Monotonic Property ◽  
Signal Processing Techniques ◽  
Special Case

The covariance matrix of signals is one of the most essential information in multivariate analysis and other signal processing techniques. The estimation accuracy of a covariance matrix is degraded when some eigenvalues of the matrix are almost duplicated. Although the degradation is theoretically analyzed in the asymptotic case of infinite variables and observations, the degradation in finite cases are still open. This paper tackles the problem using the Bayesian approach, where the learning coefficient represents the generalization error. The learning coefficient is derived in a special case, i.e., the covariance matrix is spiked (all eigenvalues take the same value except one) and a shrinkage estimation method is employed. Our theoretical analysis shows a non-monotonic property that the learning coefficient increases as the difference of eigenvalues increases until a critical point and then decreases from the point and converged to the distinct case. The result is validated by numerical experiments.

scholarly journals Optimization Of Image Processing Techniques In Developing Of Smart Parking System

2021 ◽  
Vol 3 (1) ◽  
pp. 1-4
Author(s):  
Bagus Alit Prasetyo ◽  
Ari Purno Wahyu ◽  
Suhendri Suhendri
Keyword(s):  
Image Processing ◽  
Third Party ◽  
A Algorithm ◽  
Image Processing Techniques ◽  
Parking System ◽  
Parking Lot ◽  
Smart Parking ◽  
Vision Algorithm ◽  
Processing Techniques ◽  
Sophisticated Technology

A parking system is currently a necessity and a common facility found in the campus area of buildings and shops, the management and supervision of this parking lot generally uses third party assistance both in terms of technology and facilities used. At first the parking lot system was still conventional based by using guards in front of the gate and manually recording the entry and exit of the vehicle, a more sophisticated technology was using a camera that was combined with ticketing assistance, officers would check with photos when the car entered and left and strengthened with the use parking tickets, the two technologies have been implemented in many places, the weakness of the system is that there is a need for more than one operator to record and criminal acts will be difficult to detect if a type of vehicle of the same color is stolen because the data from the photos are indistinguishable, To solve this problem, a parking system was created with the help of image processing techniques by recording different types of vehicles even though they were of the same type and color, this system worked using computer vision algorithm rocks with a combination of OCR a Algorithm and surf algorithm, these two algorithms will help record vehicle number-plates while the surf algorithm will record the unique characteristics of the vehicle object in detail so that it will not be change

A Bit-Decomposition Adaptive Watermarking Algorithm Based on the Multi-Polar Mask

2011 ◽  
Vol 467-469 ◽  
pp. 912-917
Author(s):  
Le Zhang ◽  
Quan Liu ◽  
Qi Ming Fu ◽  
Xiao Yan Wang
Keyword(s):  
Image Processing ◽  
Digital Watermarking ◽  
Image Data ◽  
Visual Quality ◽  
Human Vision ◽  
Original Image ◽  
Hidden Information ◽  
Geometric Attacks ◽  
Binary Images ◽  
Adaptive Watermarking

Traditional digital watermarking usually adopts the gray image as hidden information, more embedded information result in largely modifying more image data. Binary image can guarantee good affection of human vision, a bit-decomposition adaptive watermarking algorithm based on the mask is proposed. According to the superiority of binary, classifying binary images to three kinds of sub graph (High, Middle, and Low-sub graph); multi-masks are constructed by the importance of different sub graphs and cover the original image. Experimental results demonstrate the proposed scheme not only has better visual quality, but also is very robust to common image processing and geometric attacks.

Image Processing for Surveillance and Security

2017 ◽  
pp. 52-81 ◽  
Author(s):  
Deepayan Bhowmik ◽  
Mehryar Emambakhsh
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Digital Media ◽  
Visual Tracking ◽  
Daily Life ◽  
Fundamental Issue ◽  
Image Processing Techniques ◽  
The Media ◽  
Processing Techniques ◽  
Signal Processing Techniques

Security is a fundamental issue in today's world. In this chapter we discuss various aspects of security in daily life that can be solved using image processing techniques by grouping in three main categories: visual tracking, biometrics and digital media security. Visual tracking refers to computer vision techniques that analyses the scene to extract features representing objects (e.g., pedestrian) and track them to provide input to analyse any anomalous behaviour. Biometrics is the technology of detecting, extracting and analysing human's physical or behavioural features for identification purposes. Digital media security typically includes multimedia signal processing techniques that can protect copyright by embedding information within the media content using watermarking approaches. Individual topics are discussed referring recent literature.

A Kind of DWT Domain Image Digital Watermarking Algorithm Research

2014 ◽  
Vol 1044-1045 ◽  
pp. 991-994
Author(s):  
Tao Liu
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Frequency Domain ◽  
Digital Watermarking ◽  
Wavelet Decomposition ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Original Image ◽  
Adaptive Watermarking ◽  
Frequency Domain Methods

An image-adaptive watermarking algorithm based on wavelet transform was proposed. At first, A digital image used as watermarking was scrambled. Next, the original image was decomposed by discrete wavelet transform,and in accordance with the characteristics of human visual system, wavelet decomposition in the low-frequency domain, Methods which average of adjacent domain instead of single wavelet decomposition coefficients was used to estimate and quantitative, watermarking was adaptively embedded in wavelet coefficients of low-frequency domain. At last, the simulation experimental results show that the algorithm for a variety of conventional image processing has good robustness.

scholarly journals Pepper Powder Quality Identification System Based on Silent Angle Imagery

2020 ◽  
Vol 2 (1) ◽  
pp. 24
Author(s):  
Muhaimin Gusrin ◽  
Abdul Fadlil
Keyword(s):  
Image Processing ◽  
Research Method ◽  
Identification System ◽  
Original Image ◽  
Image Processing Techniques ◽  
Different Types ◽  
Angle Method ◽  
Pepper Powder ◽  
Processing Techniques

This research identifies the quality of pepper powder using a computer automatically. The research method uses the stationary angle method. The design of this system is done by image processing techniques. The image of ground pepper that has been taken is then cropped to remove the unused portion of the image. The next step is to convert the original image into grayscale and then convert it to binary. The parameter of the stationary angle is when it has an angle of less than or equal to 38 °, the ground pepper includes fine ground pepper. If the angle ranges from 38o to 40o, including medium powdered pepper, and if the angle is greater than 41o, including the texture of coarse pepper powder. Testing 3 different types of samples obtained 40 mesh is 35.18 o; for 20 mesh is 40.46o and 10 mesh is 41.66o. Therefore, it can be seen that the smaller the texture of the size of ground pepper, the finer the quality.Penelitian ini mengidentifikasi kualitas lada bubuk menggunakan komputer secara otomatis. Metode penelitian menggunakan metode sudut diam. Perancangan sistem ini dilakukan dengan teknik pengolahan citra. Citra lada bubuk yang telah diambil selanjutnya di-cropping untuk menghilangkan bagian citra yang tidak terpakai. Langkah selanjutnya adalah citra hasil asli tersebut dikonversi dalam bentuk grayscale dan selanjutnya dikonversi dalam bentuk biner. Parameter sudut diam adalah ketika memiliki sudut kurang dari atau sama dengan 38o, lada bubuk tersebut termasuk lada bubuk yang halus. Jika sudutnya berkisar antara 38o sampai 40o maka termasuk lada bubuk sedang, dan jika sudutnya lebih besar dari 41o maka termasuk tekstur lada bubuk kasar. Pengujian 3 jenis sampel yang berbeda didapatkan 40 mesh adalah 35,18o; untuk 20 mesh adalah 40,46o dan 10 mesh adalah 41,66o. Oleh karena itu dapat diketahui bahwa semakin kecil tekstur ukuran lada bubuk, semakin halus kualitasnya.

scholarly journals Latest advancement in image processing techniques

2018 ◽  
Vol 7 (2.12) ◽  
pp. 390
Author(s):  
V Raghavendra ◽  
N Vinay kumar ◽  
Manish Kumar
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Analog Signals ◽  
Image Characteristics ◽  
Processing Techniques ◽  
Television Image ◽  
Signal Processing Techniques ◽  
Analog Image Processing

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 processing is widely used. In the field of bio technology, computer science, in medical field, envi-ronmental areas etc., image processing is being used for mankind benefits. The following steps are the basics of image processing:Image is taken as an inputImage will be processed (manipulation, analyzing the image, or as per requirement)Altered image will be the outputImage processing is of two typesAnalog Image Processing:As the name implies, analog image processing is applied on analog signals. Television image is best example of analog signal processing [1].(DIP) Digital Image Processing:DIP techniques are used on images, which are in the format of digital for processing them, and get the required output as per the application. Operations were applied on the digital images for processing [1].In this paper, we will discuss about the technologies or tools for image processing especially by using Open CV. With the help of Open CV image processing will be very easy and efficient. When Open CV is collaborated or integrated with python the results are mind blowing. We will discuss about the process of using python and Open CV. 

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