Implementation of the watershed method in the HSI color space for the face extraction

Guerfi, Souhila; Gambotto, Jean-Pierre; Lelandais, Sylvie

doi:10.1109/avss.2005.1577281

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…The determination of pose was also done through properties of projective geometry. In another research work [17], the focus was on the color segmentation that is an important pre-processing step in the face detection methods. In this paper effective face color segmentation in the HSI (Hue, Saturation and Intensity) space is proposed which is to modify the merging algorithm of the catchment basins obtained by the watershed segmentation method by adding a criterion based on the relevance of the Hue component.…”

Section: Algorithm For Eye Trackingmentioning

confidence: 99%

Design of a graphical programming based Interactive and Computerized Eye Exercise Application

B¹

2021

Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, In

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Vision is the prominent sense of human beings and having a healthy vision becomes a prime requirement for the competitive world in modern days. Due to long time usage of computers and televisions, eye related disorders are on the rise nowadays. Physicians advise simple eye exercises like rotation and diagonal movement of eyeballs to avoid those disorders. This work is an effort to develop an interactive eye exercise regime. An object is made to move according to specific patterns on the computer screen and the eye movements of the user are recorded online. This video is then used to compare the pattern movement and eye movement and graphical result is provided to the user. This feedback may help the user in faithfully following the patterns on screen, thus completing the eye exercise in a simple but effective way.

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Section: Algorithm For Eye Trackingmentioning

confidence: 99%

Design of a graphical programming based Interactive and Computerized Eye Exercise Application

B¹

2021

Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, In

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“…The color segmentation is an important pre-processing step in the face recognition methods. We are used HIS method [5] to detection face skin color. Frist, we transform the image of RGB three color changes to H, S. It can be written as…”

Section: Skin Color Detectionmentioning

confidence: 99%

Digital Interactive Kanban Advertisement System Using Face Recognition Methodology

Cheng¹,

Chang²,

Jong³

2013

CWEEE

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Most of advertisement systems are presently still launch the publicity content by the static words and pictures. Recently, this static advertisement model will not be able to attract people's attention more and more. Moreover, the static information content of advertisement system is limited because of the layout shown size. It can not also fully demonstrate the information content of advertisement system. In this paper, we develop a digital interactive kanban advertisement system using face recognition methodology to solve these problems. The system captures the person's face through the camera. The digital advertisement content size is relevant by the person and camera observation locations. In this paper, we adopt the Adaboost algorithm to judge people face, and the system only need to grab the position of the face. The system doesn't built expensive and complex equipment to reduce the system cost and enhance the system performance. This system can also achieve the same similar digital interactive advertising effectiveness.

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“…We combine the shape and the color of the object to isolate it from the others objects. The first technique is a region segmentation using the watershed algorithm [12]. The principle of this method is to consider different sectors of the image as a whole of peaks and valleys.…”

Section: A Region Segmentation and Color Filteringmentioning

confidence: 99%

Improvements of Object Grabbing Method by Using Color Images and Neural Networks Classification

Trabelsi¹,

Ait-Oufroukh²,

Lelandais³

2006

IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics

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The works presented in this paper allow the improvement of an object grabbing method developed for the ARPH project (Robotic Assistance for Disabled people). The basic tool of this project is a mobile robot with an embedded MANUS arm. The main aim of the method developed here is to make a manipulator arm equipped with a griper and two kinds of sensors (camera and sonar) able to seizure and handle several objects in the human environment. Ultrasonic echo is recovered by a neural network classifier in order to recognize the object shape. At the same time, a little wireless HF camera takes a color image of the target, which allows to compute the coordinates of the object in the image then in the camera frame. The combination of these various information about the object with the camera geometrical model and the visual servoing principle allows to adopt an iterative strategy to approach the object under good conditions and to seize it at the end. Two kinds of object are used (spherical and cylindrical) with several colors and diameters.

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Implementation of the watershed method in the HSI color space for the face extraction

Cited by 6 publications

References 10 publications

Design of a graphical programming based Interactive and Computerized Eye Exercise Application

Design of a graphical programming based Interactive and Computerized Eye Exercise Application

Digital Interactive Kanban Advertisement System Using Face Recognition Methodology

Improvements of Object Grabbing Method by Using Color Images and Neural Networks Classification

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