Color Image Edge Detection Arithmetic Based on Color Space

Zhang, Fengjing; Hong, Cheng; Sun, Wei; Zhang, Yaoyu; Wang, Xiaojuan

doi:10.1109/iccsee.2012.186

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…The three operations are given towards the single structure element of same size. Formula (5) achieve the outside edge of image, however formula (6) achieve the inside edge, formula (7) is the continental edge. In the following, formula ( 5) is analyzed in theory: supposed 1 /2 < q 1 <q 2 < 1 and F(q, p)= f (q, p) B B, the edge of F(q 1 , p) is narrower than F(q 2 , p)'s , that is, the output of formula ( 5) is bigger along with q increasing, namely the edge becomes wider and lighter.…”

Section: Image Edge Detection Based On Order Morphological Transforma...mentioning

confidence: 99%

Weed Image Edge Detection Based on Order Morphology Transformation

Zhang

2012

AMR

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Section: Image Edge Detection Based On Order Morphological Transforma...mentioning

confidence: 99%

Weed Image Edge Detection Based on Order Morphology Transformation

Zhang

2012

AMR

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“…1 shows simulated visual images from the perspectives of people with no color blindness, red-green color blindness, blue-yellow blindness, and total color blindness. Because the accuracy of color recognition is limited by the mechanics of the human eye, this study proposes a method that uses the color sensor TCS3200 to replace manual color recognition [3]. The Espressif Systems 32 (ESP32) is connected to a Wi-Fi network, and data on color recognition, such as RGB color codes, are stored and uploaded to the ESP32 web server to establish a platform for color recognition.…”

Section: Introductionmentioning

confidence: 99%

Voice Guidance System for Color Recognition Based on IoT

Sung¹,

Chen²,

Hsiao³

2023

Computer Systems Science and Engineering

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We often need to identify the colors of such objects as buildings, clothing, photos, and traffic signs in everyday life. Some people cannot distinguish among such colors. This study proposes a method to help people, including colorblind people, identify colors. We establish a platform for color identification that is connected by the Internet of Things (IoT). The Espressif Systems 32 (ESP32) single chip is connected to a Wi-Fi communication network to transmit data to the color identification platform. The system interface is displayed in the form of color code and color name display. The speech synthesis module Speech Synthesizer Node 6288 (SYN6288) is used to broadcast color-related information. Since there are many color conversion technologies in modern times, or other color recognition methods are not applicable to the guide-blind function. Therefore, the authors use the method of reading out color-related information to directly enable colorblind people to conveniently identify the colors of objects. After experiments: the accuracy of various colors, the accuracy of environmental impact, the comparison of the original sensing experiment and the effect of adding interference light sources, the time required for color sensing to identify various colors, and the interference test results of any color light source, it is proved that the research mentioned in this research. The proposed method can not only improve the rate of recognition of the system in different environments, but can also accurately identify a variety of colors. The platform is integrated with the IoT to allow users to quickly monitor the displayed data.

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