scholarly journals A New Human Perception-Based Over-Exposure Detection Method for Color Images

Sensors ◽  
2014 ◽  
Vol 14 (9) ◽  
pp. 17159-17173 ◽  
Author(s):  
Yeo-Jin Yoon ◽  
Keun-Yung Byun ◽  
Dae-Hong Lee ◽  
Seung-Won Jung ◽  
Sung-Jea Ko
Keyword(s):  
Detection Method ◽  
Human Perception ◽  
Color Images

Edge Detection of Color Images Based on Improved Morphological Gradient Operators

2014 ◽  
Vol 511-512 ◽  
pp. 550-553 ◽  
Author(s):  
Jian Yong Liang
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Color Image ◽  
Color Images ◽  
Morphological Gradient ◽  
Image Edge Detection ◽  
Gradient Based ◽  
Image Edge ◽  
Edge Detection Method ◽  
Traditional Approaches

Edge detection is an old and hot topic in image processing, pattern recognition and computer vision. Numerous edge detection approaches have been proposed to gray images. It is difficult to extend these approaches to color image edge detection. A novel edge detection method based on mathematical morphology for color images is proposed in this paper. The proposed approach firstly compute vector gradient based on morphological gradient operators, and then compute the optimal gradient according to structure elements with different size. Finally, we use a threshold to binary the gradient images and then obtain the edge images. Experimental results show that the proposed approach has advantages of suppressing noise and preserving edge details and it is not sensitive to noise pixel. The finally edge images via the proposed method have high PSNR and NC compared with the traditional approaches.

Analysis of SSIM Based Quality Assessment across Color Channels of Images

2015 ◽  
pp. 1233-1245
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

Face Detection Based on Skin and Improved ICA

2011 ◽  
Vol 219-220 ◽  
pp. 1486-1490
Author(s):  
Yan Wang ◽  
Zheng Wu Jiang
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Detection Method ◽  
Color Space ◽  
Research Direction ◽  
Color Images ◽  
Independent Research ◽  
Image Preprocessing ◽  
In The Beginning ◽  
Speed And Accuracy

Face detection has been developed into one independent research direction. This paper proposes a detection method based on the combination of skin color and improved ICA. The method makes face detection in color images real and abandons the conventional way of detecting grey rather than color images. Its description is as follows: In the beginning, skin color mode should be founded on the basis of a new color space called H_SI_I. Then with the help of prior knowledge, image preprocessing can be implemented to obtain candidates’ faces, which will be detected by improved ICA. Experiments demonstrate that the method proposed by this paper has better effect than the conventional face detection based on subspace as far as speed and accuracy is concerned.

scholarly journals Canvas and cosmos: Visual art techniques applied to astronomy data

2017 ◽  
Vol 26 (04) ◽  
pp. 1730010 ◽  
Author(s):  
Jayanne English
Keyword(s):  
Visual Art ◽  
Human Perception ◽  
Physical Reality ◽  
Color Images ◽  
Color Theory ◽  
Electromagnetic Spectrum ◽  
Public Outreach ◽  
Black And White ◽  
Scientific Results ◽  
Technical Construction

Bold color images from telescopes act as extraordinary ambassadors for research astronomers because they pique the public’s curiosity. But are they snapshots documenting physical reality? Or are we looking at artistic spacescapes created by digitally manipulating astronomy images? This paper provides a tour of how original black and white data, from all regimes of the electromagnetic spectrum, are converted into the color images gracing popular magazines, numerous websites, and even clothing. The history and method of the technical construction of these images is outlined. However, the paper focuses on introducing the scientific reader to visual literacy (e.g. human perception) and techniques from art (e.g. composition, color theory) since these techniques can produce not only striking but politically powerful public outreach images. When created by research astronomers, the cultures of science and visual art can be balanced and the image can illuminate scientific results sufficiently strongly that the images are also used in research publications. Included are reflections on how they could feedback into astronomy research endeavors and future forms of visualization as well as on the relevance of outreach images to visual art. (See the color online PDF version at http://dx.doi.org/10.1142/S0218271817300105 ; the figures can be enlarged in PDF viewers.)

scholarly journals Restoration for blurred noisy images based on guided filtering and inverse filter

2021 ◽  
Vol 11 (2) ◽  
pp. 1265
Author(s):  
Rusul H. Altaie
Keyword(s):  
Random Noise ◽  
Human Perception ◽  
Color Images ◽  
Inverse Filtering ◽  
Inverse Filter ◽  
Guided Filtering ◽  
Different Types ◽  
Blurred Image ◽  
Blurred Images ◽  
Denoised Image

The development of complex life leads into a need using images in several fields, because these images degraded during capturing the image from mobiles, cameras and persons who do not have sufficient experience in capturing images. It was important using techniques differently to improve images and human perception as image enhancement and image restoration etc. In this paper, restoration noisy blurred images by guided filter and inverse filtering can be used for enhancing images from different types of degradation was proposed. In the color images denoising process, it was very significant for improving the edge and texture information. Eliminating noise can be enhanced by the image quality. In this article, at first, The color images were taken. Then, random noise and blur were added to the images. Then, the noisy blurred image passed to the guided filtering to get on denoised image. Finally, an inverse filter applied to the blurred image by convolution an image with a mask and getting on the enhanced image. The results of this research illustrated good outcomes compared with other methods for removing noise and blur based on PSNR measure. Also, it enhanced the image and retained the edge details in the denoising process. PSNR and SSIM measures were more sensitive to Gaussian noise than blur.

scholarly journals An Automatic Face Detection System for RGB Images

2011 ◽  
Vol 6 (1) ◽  
pp. 21 ◽  
Author(s):  
Tudor Barbu
Keyword(s):  
Face Detection ◽  
Detection Rate ◽  
Detection Method ◽  
Detection System ◽  
Color Images ◽  
Human Face ◽  
Skin Region ◽  
Detection Approach ◽  
Rgb Images ◽  
Digital Color Images

We propose a robust face detection approach that works for digital color images. Our automatic detection method is based on image skin regions, therefore a skin-based segmentation of RGB images is provided first. Then, we decide for each skin region if it represents a human face or not, using a set of candidate criteria, an edge detection process, a correlation based technique and a threshold-based method. A high face detection rate is obtained using the proposed method.

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