Novel Color Image Data Hiding Technique Based on DCT and Compressed Sensing Algorithm

2019 ◽  
pp. 1151-1157
Author(s):  
M. K. Shyla ◽  
K. B. Shiva Kumar
Keyword(s):  
Compressed Sensing ◽  
Data Hiding ◽  
Color Image ◽  
Image Data

Pencarian File Gambar Berdasarkan Dominasi Warna

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono
Keyword(s):  
Digital Image ◽  
Retrieval System ◽  
Color Image ◽  
Color Space ◽  
Image Data ◽  
Image Search ◽  
Test Results ◽  
Application Form ◽  
Space Model ◽  
Image File

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar

Color image analysis for vehicle speed measurement

1993 ◽  
Vol 20 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Yean-Jye Lu ◽  
Xidong Yuan
Keyword(s):  
Image Analysis ◽  
Traffic Control ◽  
Road Traffic ◽  
Color Image ◽  
Image Data ◽  
Difficult Problem ◽  
Vehicle Speed ◽  
Color Image Analysis ◽  
Speed Measurement ◽  
Monochrome Image

Image analysis for traffic data collection has been studied throughout the world for more than a decade. A survey of existing systems shows that research was focused mainly on the monochrome image analysis and that the field of color image analysis was rarely studied. With the application of color image analysis in mind, this paper proposes a new algorithm for vehicle speed measurement in daytime. The new algorithm consists of four steps: (i) image input, (ii) pixel analysis, (iii) single image analysis, and (iv) image sequence analysis. It has three significant advantages. First, the algorithm can distinguish the shadows caused by moving vehicles outside the detection area from the actual vehicles passing through the area, which is a difficult problem for the monochrome image analysis technique to handle. Second, the algorithm significantly reduces the image data to be processed; thus only a personal computer is required without the addition of any special hardware. The third advantage is the flexible placement of detection spots at any position in the camera's field of view. The accuracy of the algorithm is also discussed. Key words: speed measurement, vehicle detection, image analysis, image processing, traffic control, traffic measurement and road traffic.

A Multi-Party Secure Encryption-Sharing Hybrid Scheme for Image Data Base on Compressed Sensing

2022 ◽  
pp. 103391
Author(s):  
Bin Wu ◽  
Dong Xie ◽  
Fulong Chen ◽  
Xueli Wang ◽  
Yangyang Zeng
Keyword(s):  
Compressed Sensing ◽  
Data Base ◽  
Image Data ◽  
Hybrid Scheme

A Robust Reversible Data Hiding Scheme for Color Image Based on Ambtc Domain

2021 ◽  
Author(s):  
Tao Zhang ◽  
Jiantao Ding ◽  
Ruohu Ma ◽  
Yilin Wang ◽  
Zhewen Tian ◽  
...  
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Color Image

scholarly journals Reversible Data Hiding in Block Compressed Sensing Images

ETRI Journal ◽  
2016 ◽  
Vol 38 (1) ◽  
pp. 159-163 ◽  
Author(s):  
Ming Li ◽  
Di Xiao ◽  
Yushu Zhang
Keyword(s):  
Compressed Sensing ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Block Compressed Sensing

scholarly journals Survey on Image Data Hiding Based on Block Histogram Shifting Encryption Algorithm

IJARCCE ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 110-114
Author(s):  
Swapnil Singh Thakur ◽  
Prof. Amit Thakur
Keyword(s):  
Data Hiding ◽  
Image Data ◽  
Encryption Algorithm ◽  
Histogram Shifting
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