This paper proposed a new technique for image steganography using edge detection for RGB images. There are lots of algorithms to hide data with precision level but they are also decreasing the quality of the image. In this proposed study, edges of an RGB image will be detected by scanning method using 3x3 window, and then text will be embedded in to the edges of the color image. By doing this n...

The paper presents a concept for generated motion maps to directly generate a human-specific modality such as human pose and stacked optical flow, with only one rgb-image. Although the conventional approaches have achieved a complicated estimation with a discriminative model, we find the solution with a recent generative model. The two primary contributions in this paper are as follows: (i) pro...

Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attenti...

This paper presents an IF1F2 color space for describing colors in microscopic images. Unlike the classical color spaces that treat the R, G, and B (RGB) components of a pixel’s color as independent elements, the proposed color space treats RGB as a sampled spectral signal, called a RGB signal. Then, based on the Fourier spectrum analysis of the RGB signal, the 1-D discrete Fourier transform is ...

This paper proposes a deep neural network (DNN) for piece-wise planar depthmap reconstruction from a single RGB image. While DNNs have brought remarkable progress to single-image depth prediction, piece-wise planar depthmap reconstruction requires a structured geometry representation, and has been a difficult task to master even for DNNs. The proposed end-to-end DNN learns to directly infer a s...

With the rapid growth of qubit numbers and coherence times in quantum hardware technology, implementing shallow neural networks on so-called Noisy Intermediate-Scale Quantum (NISQ) devices has attracted a lot interest. Many (convolutional) circuit ansaetze are proposed for grayscale images classification tasks with promising empirical results. However, when applying these RGB images, intra-chan...

Image enhancement can improve the perception of information for human viewers, which is also a basic and pretty significant role in image processing. However, there also exist some limitations in most image enhancement algorithms. In this paper discuss the limitations of existing techniques of image enhancement. In order to solve the limitations well, a novel sparse code fusion (SCF) method is ...

This research features a new method for skin color segmentation using a 2D plane in the RGB color space. The RGB color values of the input color image do not need to be converted into HSI or YIQ color coordinates that have popularly been used for color segmentation. We have observed an important fact that skin colors in the RGB color space are approximately distributed in a linear fashion. Base...

BACKGROUND There is a subjective disagreement about nuclear chromatin in the field of pathology. Objective values of red, green, and blue (RGB) light intensities for nuclear chromatin can be obtained through a quantitative analysis using digital images. METHODS We examined 10 cases of well differentiated neuroendocrine tumors of the rectum, small cell lung carcinomas, and moderately different...

Hartley, Cosine, Slant and Haar Transforms for Grayscale Image Colorization Using Thepade‟s Transform Error Vector Rotation(TTEVR) Algorithms of Vector Quantization in YIQ, RGB and YCbCr color spaces are compared here for color pallet(codebook) size 32, 64, 128, 256 and 512. Here a color pallet is produced from reference(color) image from which color traits need to be taken using vector quantiz...