An efficient image retrieval based on HSV color space

Su, Ching-Hung; Chiu, Huang-Sen; Hsieh, Tsai-Ming

doi:10.1109/iceceng.2011.6058026

Cited by 32 publications

(23 citation statements)

References 6 publications

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“…The HSV stands for the Hue, Saturation and Value. The HSV components correspond more closely to human-perceived qualities of a colour than the RGB components [16], so it is widely used for human hand or face detection. However, HSV values are also affected by screen colors sometimes, so we came up with the idea of using both HSV and RGB models, and it works well.…”

Section: Locating the Fingertip In The Camera Imagementioning

confidence: 99%

Transforming a Regular Screen Into a Touch Screen Using a Single Webcam

Zhang

Saboune

Saddik

2014

J. Display Technol.

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Nowadays, touch screens are widely used in many commercial devices. In this paper, we present an inexpensive webcam-based touch screen system based on a simple and generic finger detection technique. Only a single webcam and a regular screen are used to achieve this goal. By using the scene geometry and the camera model, we can determine the position of the finger on the screen. The technique we propose is simple and works well under various surrounding environments while the detecting method suits many finger colors and shapes. Our approach can also be used for realtime applications. Experimental results and practical applications are provided to ascertain the proposed method.

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Section: Locating the Fingertip In The Camera Imagementioning

confidence: 99%

Transforming a Regular Screen Into a Touch Screen Using a Single Webcam

Zhang

Saboune

Saddik

2014

J. Display Technol.

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“…Step 4: Each P i shares her ciphertext C i with other participants and calculates the product of all ciphertexts according to Equation (5) to obtain the value of C.…”

Section: Secure Multi-party Computationmentioning

confidence: 99%

“…In early years, textbased image retrieval systems implemented by manual tagging image properties could fulfill the requirement of image retrieval. With the growing popularity of Internet users, hundreds of millions of images appear on the Internet per second, the traditional text-based image retrieval becomes gradually impractical, because it consumes prohibitive manpower and financial resources for labeling.. Content-based image retrieval (CBIR) [1][2][3] has been proposed for real world applications which uses the image feature extracted automatically from images, such as colors [4,5], textures [6,7], and shapes [8,9].…”

Section: Introductionmentioning

confidence: 99%

Content-based multi-source encrypted image retrieval in clouds with privacy preservation

Shen

Cheng

Zhu

et al. 2020

Future Generation Computer Systems

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Content-based image retrieval (CBIR) is one of the fundamental image retrieval primitives. Its applications can be found in various areas, such as art collections and medical diagnoses. With an increasing prevalence of cloud computing paradigm, image owners desire to outsource their images to cloud servers. In order to deal with the risk of privacy leakage of images, images are typically encrypted before they are outsourced to the cloud, which makes CBIR an extremely challenging task. Existing studies focus on the scenario with only a single image owner, leaving the problem of CBIR with multiple image sources (i.e., owners) unaddressed.In this paper, we propose a secure CBIR scheme that supports Multiple Image owners with Privacy Protection (MIPP). We encrypt image features with a secure multi-party computation technique, which allows image owners to encrypt image features with their own keys. This enables efficient image retrieval over images gathered from multiple sources, while guaranteeing that image privacy of an individual image owner will not be leaked to other image owners. We also propose a new method for similarity measurement of images that can avoid revealing image similarity information to the cloud. Theoretical analysis and experimental results demonstrate that MIPP achieves retrieval accuracy and efficiency simultaneously, while preserving image privacy.

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“…Color can be described in many different ways [17,18]. The color model is called color space, and the color space is capable of rendering all color sets; it is based on some standard values to describe color; basically, the color model is composed of three-dimensional coordinates and a sub-space; in this subspace, each color is represented by a point.…”

Section: Color Modelmentioning

confidence: 99%

Palm Personal Identification for Vehicular Security with a Mobile Device

Hsu

Lee

Tseng

et al. 2013

International Journal of Vehicular Technology

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Security certification is drawing more and more attention in recent years; the biometric technology is used in a variety of different areas of security certification. In this paper, we propose a palm image recognition method to identify an individual for vehicular application; it uses palm image as a key for detecting the car owner. We used mobile phone cameras to take palm images and performed a new identification approach by using feature regularization of palm contour. After identification is confirmed, the phone uses Bluetooth/WiFi to connect the car to unlock it. In our evaluation, the experiments show that our approach is effective and feasible.

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An efficient image retrieval based on HSV color space

Cited by 32 publications

References 6 publications

Transforming a Regular Screen Into a Touch Screen Using a Single Webcam

Transforming a Regular Screen Into a Touch Screen Using a Single Webcam

Content-based multi-source encrypted image retrieval in clouds with privacy preservation

Palm Personal Identification for Vehicular Security with a Mobile Device

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