An underwater-imaging-model-inspired no-reference quality metric for images in multi-colored environments

Luo, Zhihang; Tang, Zhijie; Jiang, Lizhou; Wang, Chi

doi:10.1016/j.eswa.2021.116361

Cited by 12 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The image of the caputure zoom result is a color image (RGB). To process the image of a colored image (RGB) is converted to a gray image [16]. The command to convert a color image (RGB) into a gray image is as follows:…”

Section: Methodsmentioning

confidence: 99%

Image Edge Detection Capture Zoom for Facial Recognition Using Gradient Operators

Hadi

Sumijan

2022

komtekinfo

View full text Add to dashboard Cite

Imagery on edge detection is a process that will display the edges of an image. Basically, edge detection is one of the techniques for the analysis of image quality in the spatial domain and is also one of the initial process in digital image processing. Edge detection serves to detect the border line of an object contained in the image. This study aims to identify and recognize face pattern objects in the capture zoom image. To perform face identification begins with collecting image data, image processing, image edge detection, thinning of the image, and identification process using the template matching method. The method used in edge detection uses 3 methods, namely Sobel, Roberts and Prewitt which are gradient operators to detect edges in facial images. The dataset used is image capture zoom. The trial was carried out in two stages, namely the identification of the face shape and the identification of the edges of the face. The conclusion of the study is that the Roberts operator is the operator that finds the least edge patterns in facial images than the other two operators, namely Prewitt and Sobel. Meanwhile, the Sobel operator produces edge patterns that are better in quality and quantity than using the Roberts and Prewitt operators.

show abstract

Section: Methodsmentioning

confidence: 99%