Integer-based accurate conversion between RGB and HSV color spaces

Chernov, Vladimir; Alander, Jarmo T.; Bochko, Vladimir

doi:10.1016/j.compeleceng.2015.08.005

Cited by 141 publications

(80 citation statements)

References 4 publications

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“…(2) Extraction of the "Value" plane from RGB to HSV color space conversion for better extraction of edge line and laser line [19]. RGB color space describes colors in terms of the amount of Red, Green, and Blue planes.…”

Section: Methodsmentioning

confidence: 99%

A Computer Vision Based Conveyor Deviation Detection System

Zhang

Shi

et al. 2020

Applied Sciences

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The monitoring of conveyor belt deviation based on computer vision is the research topic of this paper. A belt conveyor system equipped with cameras and a laser generator is used as the test apparatus. Two kinds of conveyor condition monitoring algorithms are developed, applied and compared in this paper. Method 1 is to extract the edges of the conveyor belt based on the methods of edge detection and line fitting, and an analysis method is proposed to quickly determine whether the conveyor belt is off course. This method simplifies the information processing process after edge line extraction and realizes the fast and effective state detection of the conveyor belt. A conveyor belt deviation detection system was built in Method 2 with the aid of laser technology and the Labview platform. The result of deviation detection was more accurate and reliable with the addition of the laser line. It is observed that both methods can perform well for belt deviation detection, especially Method 2 that resulted in higher reliability and accuracy with faster processing speed. It provides new ideas for ensuring the safe and efficient operation of the conveyor.

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Section: Methodsmentioning

confidence: 99%

A Computer Vision Based Conveyor Deviation Detection System

Zhang

Shi

et al. 2020

Applied Sciences

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“…The area of color's usage can be described using the red-green-blue (RGB) color model or HSV color model. Chernov et al 42 present the transformation equations for the conversion between the RGB and HSV models (1) to (5). The most crucial factor in an industrial environment is the effect of the brightness.…”

Section: Vision Systemmentioning

confidence: 99%

Intelligent Selective Compliance Articulated Robot Arm robot with object recognition in a multi-agent manufacturing system

Zakhama

Charrabi

Jelassi

2019

International Journal of Advanced Robotic Systems

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Nowadays, industry tends to adopt the smart factory concept in their production. Technology intelligence is applied to use all the resources efficiently. Robots and vision system are masters in this kind of industry. However, information transfer between the robot controller and the vision system poses a great challenge. Data exchange between these two systems shall be secure, and the transfer must be with a very high level of accuracy. In this article, a multi-platform software application using a vision system is performed to control a Selective Compliance Articulated Robot Arm robot. The software solution includes the detection of defaults in a product by calculating a compliance rate using an efficient algorithm. An analysis of four different algorithms related to histogram-based similarity functions is set. Then, the most efficient algorithm is integrated into the application that provides a secure communication between three different operating systems. Experiments in a multi-agent manufacturing center validate the effectiveness of the proposed method. Tests demonstrate the efficiency of the data transfer between the vision system and the multi-platform software application and the Selective Compliance Articulated Robot Arm robot. This data transfer can be controlled in a high accuracy manner without any additional manual parameters tuning.

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“…(3) Saturation mask The hue, saturation, and value (HSV) space can intuitively express the shades and vividness of colors and facilitate comparisons between colors [27]. When obtaining the saturation mask, this work first converts the image to be calibrated from the RGB space to the HSV space and then uses the same method as that used for the chroma mask to determine a saturation threshold of the image of 0.2012.…”

Section: Automatic Identification and Calibration Of Earth Layer Flakmentioning

confidence: 99%

Improved region growing algorithm for the calibration of flaking deterioration in ancient temple murals

Cao

Cui

et al. 2018

Herit Sci

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Ancient murals are vulnerable to varying degrees of damage due to long-term exposure to external environmental factors such as light, temperature and humidity. Enabling people to appreciate the original features of murals has become a concern for field experts. The development of computer technology makes it possible to use intelligent information processing to simulate and restore ancient murals. This paper proposes an improved region growing algorithm based on threshold segmentation to automatically calibrate the flaking-related deterioration of murals in response to erosion by taking temple murals from the Song Dynasty in Kaihua Temple as the study object. First, we analyze the color characteristics of the flaking area, mark the suspected flaking-damaged points by threshold segmentation, and use these points as seeds for the area growth and expansion of the flaking area. We then calculate the color mask. Next, in the YCbCr and HSV color spaces, the brightness, chroma, and saturation characteristics of the flaking area are analyzed. The masks for the brightness, chroma, and saturation of the flaking area are obtained by threshold segmentation, and all the feature masks are merged. Finally, the mask of the flaking area obtained by data fusion is added to the original image to calibrate the flaking deterioration. Compared with current calibration algorithms based on multiscale mural deterioration, the experimental results show that the average error and error standard deviation of the proposed calibration algorithm are 1.91 and 1.82, respectively, without noise and 1.97 and 1.85, respectively, with noise. The errors are reduced, and the calibration performance is improved and stable. This work provides a good foundation for the virtual and practical restoration of ancient murals.

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Integer-based accurate conversion between RGB and HSV color spaces

Cited by 141 publications

References 4 publications

A Computer Vision Based Conveyor Deviation Detection System

A Computer Vision Based Conveyor Deviation Detection System

Intelligent Selective Compliance Articulated Robot Arm robot with object recognition in a multi-agent manufacturing system

Improved region growing algorithm for the calibration of flaking deterioration in ancient temple murals

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