A Novel Color Image Watermarking Method based on Digital Wavelet Transform and Hungarian Algorithms

3D printing has recently been applied to many areas of life including education, healthcare, aerospace, automotive, industrial design and other domains in industry. Due to the fact that the benefit of 3D printing is significant, the copyright issue of 3D printing has been become essentially and importantly. To solve the copyright issue of 3D printing, we would like to propose a 3D printing watermarking algorithm based on the mean distance of 2D slices in this paper. In the proposed method, 3D printing model is sliced into a set of 2D slices, and each 2D slice is then embedded a bit of watermark data by changing the length of mean distance of that slice. Finally, the coordinates of points in each 2D slice will be altered according to the changed mean distance value of 2D slice which has been embedded watermark bit. Experimental results showed that the mean distance error between the watermarked 2D slices and the original 2D slices is very small. The bit error rate (BER) between the extracted watermark and the original watermark is also very low. So, we verify that the invisibility of the proposed method is effective, and the proposed method is also robust to geometric attacks as rotation, scaling, and translation. Comparing to the conventional works, the proposed method also provides a solution with better accuracy.

Section: D Model Watermarkingmentioning

confidence: 99%

3D Printing Watermarking Algorithm Based on 2D Slice Mean Distance

Tran¹

2020

“…Digital watermarking has contributed to address this issue but not up to the mark due to practical difficulties since digital watermarking can be done only at the time of the capturing/recording of an image [1]. This drawback is predominantly dealt by passive techniques where some clues available about the tampering not visible like watermark [2]. Image forgery classified into three categories, they are Image retouching, image splicing and copy-move [3].…”

Section: Introductionmentioning

confidence: 99%

Copy Move Forgery Detection Using Hybrid Algorithm

Rao¹

2020

Image forgery detection in terms of copy-move detection is an emerging area for researchers in recent times. This paper proposes the combined methodology of Saliency detection and Local binary pattern-based forgery detection for real time images. Saliency detection is used to identify the forged portion on a preliminary step. It locks the region of the tampered portion with surrounding (global) area. Then, the exact pixels/region is identified or captured by Local Binary Pattern features for the tampered portions. This combined approach maintains the advantages of both saliency map and Local Binary Pattern particularly in scaling/rotation with fast detection rate than the existing methods. In addition to the existing outcome of forgery detection, the proposed method accurately identifies the forged region with depth map information. The severity of the tampered portion is examined with reference to the bits/pixel. The novelty in the proposed method lays the way of detecting the tampered portion in the real-time digital image. The state of art comparison is also proved that the proposed method is far better than existing methods.

“…Images were taken using a smart phone with 16-Mega (f/1.9, 1.12-micron) rare camera. Digital images can be easily captured and stored everywhere [13] the light inside the box should be at least 3300 lumens for better visualization of the internal quality of the eggs. It consists of four warm white bulbs and surrounded by an aluminum foil for proper light distribution.…”

Section: Introductionmentioning

confidence: 99%

An Image Processing Approach of Multiple Eggs’ Quality Inspection

Alon¹,

Marasigan²,

Nicolas-Mindoro³

et al. 2019

The current system of checking and grading egg quality in the Philippines was done manually one by one using the traditional way where graders exert great effort that resulted in graders' visual stress. To address the problem identified the researchers proposed a scientific way of checking and grading the egg quality by using image processing based non-destructive and cost-effective technique to detect various cracks, dirt, and defect in eggs. Upon testing, the system obtained a total of 91.33% as high-quality eggs and the presence of either crack or dirt while 8.66% were inspected as low quality. For the internal part of each egg, the system achieved 100% detection of the yolk. The main results achieved have been quite promising; the researchers are encouraged to continue the labor of improving the generation of internal and external egg detection.