scholarly journals Special Issue on “Advances in Image Processing, Analysis and Recognition Technology”

2020 ◽  
Vol 10 (21) ◽  
pp. 7582
Author(s):  
Dariusz Frejlichowski

For many decades researchers have been trying to make computer analysis of images as effective as the human vision system is [...]

Author(s):  
Ruchir Shah ◽  
Dhaval Tamboli ◽  
Ajay Makwana ◽  
Ravindra Baria ◽  
Kishori Shekokar ◽  
...  

In this survey paper, we have discussed a proposed system that can be a visionary eye for a blind person. A common goal in computer vision research is to build machines that can replicate the human vision system. For example, to recognize and describe objects/scenes. People who are blind to overcome their real daily visual challenges. To develop a machine that can work by the vocal and graphical assistive answer. A machine can work on voice assistant and take the image taken by a person and after an image processing and extract the result after neural networks.


Author(s):  
Xiangyang Xu ◽  
Qiao Chen ◽  
Ruixin Xu

Similar to auditory perception of sound system, color perception of the human visual system also presents a multi-frequency channel property. In order to study the multi-frequency channel mechanism of how the human visual system processes color information, the paper proposed a psychophysical experiment to measure the contrast sensitivities based on 17 color samples of 16 spatial frequencies on CIELAB opponent color space. Correlation analysis was carried out on the psychophysical experiment data, and the results show obvious linear correlations of observations for different spatial frequencies of different observers, which indicates that a linear model can be used to model how human visual system processes spatial frequency information. The results of solving the model based on the experiment data of color samples show that 9 spatial frequency tuning curves can exist in human visual system with each lightness, R–G and Y–B color channel and each channel can be represented by 3 tuning curves, which reflect the “center-around” form of the human visual receptive field. It is concluded that there are 9 spatial frequency channels in human vision system. The low frequency tuning curve of a narrow-frequency bandwidth shows the characteristics of lower level receptive field for human vision system, the medium frequency tuning curve shows a low pass property of the change of medium frequent colors and the high frequency tuning curve of a width-frequency bandwidth, which has a feedback effect on the low and medium frequency channels and shows the characteristics of higher level receptive field for human vision system, which represents the discrimination of details.


2012 ◽  
Vol 157-158 ◽  
pp. 410-414 ◽  
Author(s):  
Ji Feng Xu ◽  
Han Ning Zhang

The relationship between modern furniture color image and eye tracking has been of interest to academics and practitioners for many years. We propose and develop a new view and method exploring these connections, utilizing data from a survey of 31 testees’ eye tracking observed value. Using Tobii X120 eye tracker to analyze eye movement to furniture samples in different hue and tones colors, we highlight the relative importance of the effect of furniture color on human vision system and show that the connections between furniture color features with color image.


2009 ◽  
Vol 09 (04) ◽  
pp. 495-510 ◽  
Author(s):  
WEIREN SHI ◽  
ZUOJIN LI ◽  
XIN SHI ◽  
ZHI ZHONG

The human vision system is a very sophisticated image processing and objects recognition mechanism. However, it is a challenge to simulate the human or animal vision system to automate visual function in machines, because it is difficult to account for the view-invariant perception of universals such as environmental objects or processes and the explicit perception of featural parts and wholes in visual scenes. In this paper, we first present an introduction to the importance of biologically inspired computer vision and review general and key vision functions from neuroscience perspective. And most significantly, we give an important summarization to and discussion on the specific applications of biologically inspired modeling, including biologically inspired image pre-processing, image perception, and objects recognition. In the end, we give some important and challenging topics of computer vision for future work.


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