Analysis of the Difference in Color Image Preference According to the Dining Space Image Style

2021 ◽  
Vol 12 (5) ◽  
pp. 2937-2950
Author(s):  
Mija Kim
Keyword(s):  
Color Image ◽  
The Difference ◽  
Space Image

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.

Hybrid Method for Vehicle Detection from CCTV Captured Image

2013 ◽  
Vol 677 ◽  
pp. 412-417
Author(s):  
Suppatoomsin Chompoo ◽  
Srikaew Arthit
Keyword(s):  
Hybrid Method ◽  
Color Image ◽  
Principal Component ◽  
Vehicle Detection ◽  
Self Organizing Map ◽  
Resonance Theory ◽  
Difference Image ◽  
Fuzzy Art ◽  
Image Area ◽  
The Difference

This paper presents a hybrid method for vehicle detection from CCTV captured image. In order to overwhelm such complex details of the color image, the system combines artificial intelligence techniques to achieve automatic vehicle detection. These are techniques 2D principal component analysis (2DPCA), Fuzzy adaptive resonance theory (Fuzzy ART), genetic algorithm (GA) and self-organizing map. The proposed system can detect different vehicle sizes from different proportional image area. Bilinear interpolation is used to resize each proportional image area to vehicle feature matrix. The proposed system can detect various types of vehicles from the difference image background.

Study on Moving Object Detection Based on RGB Color Model

2013 ◽  
Vol 710 ◽  
pp. 700-703
Author(s):  
Chun Yang Liu ◽  
Dao Zheng Hou ◽  
Chang An Liu
Keyword(s):  
Difference Method ◽  
Moving Objects ◽  
Color Image ◽  
Three Dimensional ◽  
Color Model ◽  
Current Frame ◽  
Gray Image ◽  
Average Value ◽  
The Difference ◽  
Background Difference

The traditional background difference method is based on gray image. Some information is lost when color image is transformed into gray image. So it is difficult to discriminate different colors with similar gray values and easily disturbed by noise and shadows. In this paper, the background difference is based on RGB color model. It is proposed to use the average value of each pixel of the color image sequences to extract the background, and then use the three-dimensional color values of the current frame and background image to compute the difference to detect the moving objects. The proposed approach is simple and easy to implement. The experimental results show that it is more sensitive to colors and has higher accuracy and robustness than the traditional background difference method. Besides, it is more resistant to shadows.

ROBUST EYE FEATURE EXTRACTION FROM FACIAL COLOR IMAGE USING IRIS COLOR COMPENSATION

2012 ◽  
Vol 26 (01) ◽  
pp. 1256004
Author(s):  
VAN HUAN NGUYEN ◽  
HAKIL KIM
Keyword(s):  
Feature Extraction ◽  
Color Image ◽  
Least Mean Square ◽  
Iris Color ◽  
Feature Spaces ◽  
Show Evidence ◽  
Color Compensation ◽  
Novel Method ◽  
The Difference ◽  
Difference Images

This paper presents a novel method of robust eye feature extraction from facial color images by considering the variety of iris colors. Given an eye window containing a single eye, the proposed method assesses the iris color tone based on the difference images between the red and the green channels and the red and the blue channels. A weighted scaling compensation method is then proposed for increasing the separability and homogeneity of the iris region. The extraction of the eye features is performed by an unsupervised K-means clustering on the compensated feature spaces. The eye corners are detected after eyelid fitting using a least mean square cost function. Experiments on a collection of eye images extracted from the FERET face database show evidence of promising performance from color facial images with variation in illumination, pose, eye gazing direction, and race.

scholarly journals Watermarking Video Menggunakan Metode Transformasi Wavelet Diskrit

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Syamsuryadi Syamsuryadi ◽  
Ibnu Aqil
Keyword(s):  
Color Image ◽  
Video Quality ◽  
Extraction Process ◽  
Video Watermarking ◽  
Quality Analysis ◽  
Discrete Wavelet ◽  
Original Video ◽  
Binary Images ◽  
Video Watermark ◽  
The Difference

<p align="center"><strong><em>Abstract</em></strong></p><p><em>Watermarking videos are useful to determine authentication rights to a video. The step of watermarking is by inserting binary images on an MPEG1 format video using discrete wavelet transformations, and extracting watermark videos. Analysis of video watermark quality can be known by calculatong PSNR. Video watermark quality analysis is done after carrying out the watermarking and extraction process to find out the difference the original video quality and the video watermark and the insertion image used. The results of video watermark quality analysis showed that 100% video watermarks did not change from the original video and binary imagery was better than the color image in the insert image.</em></p><p><strong><em>Keyword </em></strong><em>: video watermarking, authentication, binary imagery, insert image, discrete wavelet transformation, PSNR.</em></p><p align="center"><strong><em>Abstrak</em></strong></p><p><em>Watermarking video berguna untuk menentukan hak otentikasi terhadap suatu video. Tahapan watermarking adalah penyisipan citra biner terhadap suatu video berformat MPEG1 menggunakan transformasi wavelet diskrit, dan melakukan ekstraksi terhadap video watermark. Analisis kualitas video watermark dapat diketahui dengan perhitungan PSNR. Analisis kualitas video watermark dilakukan setelah melakukan proses watermarking dan ekstraksi untuk mengetahui apakah perbedaan  kualitas video asli dengan video watermark dan citra sisipan yang digunakan. Hasil analisis kualitas video watermark menunjukkan bahwa 100% video watermark tidak mengalami perubahan dari video asli dan citra biner lebih baik daripada citra berwarna pada citra sisipan.</em></p><p><strong><em>Kata kunci </em></strong><em>: watermarkingi video, otentikasi, citra biner, citra sisipan, transformasi wavelet diskrit, PSNR. </em></p>

scholarly journals COLOR IMAGES

2011 ◽  
Vol 21 (4) ◽  
pp. 61 ◽  
Author(s):  
Dominique Lafon ◽  
Tahiana Ramananantoandro
Keyword(s):  
Color Image ◽  
Dimensional Space ◽  
Color Images ◽  
Color Measurement ◽  
Material Surface ◽  
Measuring Instruments ◽  
Measurement Systems ◽  
Whole Process ◽  
The Difference ◽  
Color Texture

The goal of this article is to present specific capabilities and limitations of the use of color digital images in a characterization process. The whole process is investigated, from the acquisition of digital color images to the analysis of the information relevant to various applications in the field of material characterization. A digital color image can be considered as a matrix of pixels with values expressed in a vector-space (commonly 3 dimensional space) whose specificity, compared to grey-scale images, is to ensure a coding and a representation of the output image (visualisation printing) that fits the human visual reality. In a characterization process, it is interesting to regard color image attnbutes as a set of visual aspect measurements on a material surface. Color measurement systems (spectrocolorimeters, colorimeters and radiometers) and cameras use the same type of light detectors: most of them use Charge Coupled Devices sensors. The difference between the two types of color data acquisition systems is that color measurement systems provide a global information of the observed surface (average aspect of the surface): the color texture is not taken into account. Thus, it seems interesting to use imaging systems as measuring instruments for the quantitative characterization of the color texture.

Fractional two-dimensional discrete chaotic map and its applications to the information security with elliptic-curve public key cryptography

2017 ◽  
Vol 24 (20) ◽  
pp. 4797-4824 ◽  
Author(s):  
Zeyu Liu ◽  
Tiecheng Xia ◽  
Jinbo Wang
Keyword(s):  
Elliptic Curve ◽  
Color Image ◽  
Chaotic Map ◽  
Public Key Cryptography ◽  
Public Key ◽  
Phase Portraits ◽  
Largest Lyapunov Exponent ◽  
Two Dimensional ◽  
Function Combination ◽  
The Difference

A novel fractional two-dimensional triangle function combination discrete chaotic map is proposed by use of the discrete fractional calculus. The chaos behaviors are then discussed when the difference order is a fractional one. The bifurcation diagrams, the largest Lyapunov exponent and the phase portraits are displayed, especially, the elliptic curve public key cryptosystem is used in color image encryption algorithm.

Automatic White Balance of Digital Camera Based on Global Probability Distribution

2012 ◽  
Vol 433-440 ◽  
pp. 5443-5447 ◽  
Author(s):  
Hui Nan Guo ◽  
Jian Zhong Cao
Keyword(s):  
Probability Distribution ◽  
Color Image ◽  
Digital Camera ◽  
Light Sources ◽  
Digital Cameras ◽  
White Balance ◽  
Hsi Color Model ◽  
The Difference ◽  
True Colors ◽  
Automatic White Balance

The white balance is an important parameter of digital camera which makes a great impact on the application of digital cameras. However, due to the limitations of hardware of digital camera, the output image of digital camera cannot restore true colors of the objects under the different light sources conditions. And existing automatic white balance (AWB) algorithms have many application restrictions, particularly the single color image, the algorithms always failure to adjust. To solve this problem, this paper proposes an optimized algorithm based on the gray world assumption and HSI color model. According to the R, G and B color components probability distribution, the algorithm adjusts the image by using the difference value of color. Experimental results show that our algorithm can adjust images in complex situations; meanwhile these confirm that this method is not only effective, but also has the advantage of easy realization.

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