3D Hand Reconstruction from a RGB Image

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

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Variable Precision Depth Encoding for 3D Range Geometry Compression

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.17.3dmp-034 ◽

2020 ◽

Vol 2020 (17) ◽

pp. 34-1-34-7

Author(s):

Matthew G. Finley ◽

Tyler Bell

Keyword(s):

Normal Distribution ◽

Arbitrary Distribution ◽

File Size ◽

Geometry Compression ◽

Variable Precision ◽

Wide Range ◽

Novel Method ◽

Encoding Method ◽

Rgb Image ◽

Color Channels

This paper presents a novel method for accurately encoding 3D range geometry within the color channels of a 2D RGB image that allows the encoding frequency—and therefore the encoding precision—to be uniquely determined for each coordinate. The proposed method can thus be used to balance between encoding precision and file size by encoding geometry along a normal distribution; encoding more precisely where the density of data is high and less precisely where the density is low. Alternative distributions may be followed to produce encodings optimized for specific applications. In general, the nature of the proposed encoding method is such that the precision of each point can be freely controlled or derived from an arbitrary distribution, ideally enabling this method for use within a wide range of applications.

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Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.21 ◽

2017 ◽

Vol 7 (8) ◽

pp. 56

Author(s):

Ashish Dwivedi ◽

Nirupma Tiwari

Keyword(s):

Image Enhancement ◽

Color Image ◽

Human Perception ◽

Histogram Equalization ◽

Wavelet Shrinkage ◽

Visual Appearance ◽

Enhancement Method ◽

Fuzzy Histogram ◽

Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

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