gait contains important information about the status of the human body and physiological signs. in many medical applications, it isimportant to monitor and accurately analyze the gait of the patient. since walking shows the reproducibility signs in several phases,separating these phases can be used for the gait analysis. in this study, a method based on image processing for extracting phases of...

The biophysical properties of a crop are good indicator potential stress conditions. However, these visible cannot indicate areas exhibiting non-visible stress, e.g., early water or nutrient stress. In this research, maize including canopy height and Leaf Area Index (LAI), estimated using drone-based RGB images, were used to identify stressed in the farm. First, APSIM process-based model was si...

The consolidation of unmanned aerial vehicle (UAV) photogrammetric techniques for campaigns with high and medium observation scales has triggered the development new application areas. Most these vehicles are equipped common visible-band sensors capable mapping areas interest at various spatial resolutions. It is often necessary to identify vegetated masking purposes during postprocessing phase...

Space situational awareness (SSA) system requires recognition of space objects that are varied in sizes, shapes, and types. The images challenging because several factors such as illumination noise thus make the task complex. Image fusion is an important area image processing for various applications including RGB-D sensor fusion, remote sensing, medical diagnostics, infrared visible fusion. Re...

We present BV photometry of the Sculptor dwarf galaxy to V = 22. These data give evidence for a bimodality in Sculptor’s metallicity distribution based on a discontinuity in the luminosities of horizontal branch (HB) stars and by the presence of two distinct red giant branch (RGB) bumps. A consistent picture of the evolved stars in Sculptor is given by the presence of (1) a metal-poor populatio...

In this paper we propose a multispectral image compression based on lossy to lossless coding, suitable for both spectral and color reproduction. The proposed method divides a multispectral image data into two groups, RGB and residual. The RGB component is extracted from the multispectral image, for example, by using the XYZ Color Matching Functions, a color conversion matrix, and a gamma curve....

This paper studies the problem of RGB-D object recognition. Inspired by the great success of deep convolutional neural networks (DCNN) in AI, researchers have tried to apply it to improve the performance of RGB-D object recognition. However, DCNN always requires a large-scale annotated dataset to supervise its training. Manually labeling such a large RGB-D dataset is expensive and time consumin...