Douglas Chai

Face segmentation using skin-color map in videophone applications

This paper addresses our proposed method to automatically segment out a persons face from a given image that consists of a head-and-shoulders view of the person and a complex background scene. The method involves a fast, reliable, and effective algorithm that exploits the spatial distribution characteristics of human skin color. A universal skin-color map is derived and used on the chrominance component of the input image to detect pixels with skin-color appearance. Then, based on the spatial distribution of the detected skin-color pixels and their corresponding luminance values, the algorithm employs a set of novel regularization processes to reinforce regions of skin-color pixels that are more likely to belong to the facial regions and eliminate those that are not. The performance of the face-segmentation algorithm is illustrated by some simulation results carried out on various head-and-shoulders test images. The use of face segmentation for video coding in applications such as videotelephony is then presented. We explain how the face-segmentation results can be used to improve the perceptual quality of a videophone sequence encoded by the H.261-compliant coder.

Locating facial region of a head-and-shoulders color image

This paper addresses our proposed method to automatically locate the persons face from a given image that consists of a head-and-shoulders view of the person and a complex background scene. The method involves a fast, simple and yet robust algorithm that exploits the spatial distribution characteristics of human skin color. It first uses the chrominance component of the input image to detect pixels with skin color appearance. Then, bused on the spatial distribution of the detected skin-color pixels and their corresponding luminance values, the algorithm employs some regularization processes to reinforce regions of skin-color pixels that are more likely to belong to the facial regions and eliminate those that are not. The performance of the face localization algorithm is illustrated by some simulation results carried out on various head-and-shoulders test images.

Foreground/background video coding scheme

This paper presents the use of segmentation to improve the subjective quality of the sequence produced by very low bit rate video coding system. Through this approach, each frame of the source sequence is first segmented into two non-overlapping regions, namely foreground and background. These two regions are then encoded using the same coder but with different quantization step-sizes. In this way, the image quality of the foreground region can be improved at the expense of encoding the unimportant background region at lower quality. Currently, our work focuses on integrating this approach into the H.263 coder, primarily for the videotelephony application. In this paper, we describe the working implementation, and also demonstrate the improved subjective quality of the coded sequence achieved.

Barcodes for Mobile Devices

From inventory management in stores to automotive part tracking in assembly plants, barcodes are one of the most prevalent automatic identification and data capture technologies. This book provides a complete introduction to barcodes for mobile devices, presenting the most relevant and up-to-date information previously unavailable elsewhere or difficult to obtain. The focus throughout is on recent developments and two-dimensional (2D) barcodes, including the research and development steps towards colour barcodes for mobile devices, helping readers to develop their own barcodes. The authors also provide design details for their own novel colour 2D barcode: the Mobile MultiColour Composite (MMCC) barcode, plus coverage of RFID technology and one-dimensional barcodes. This book is ideal for professional developers of barcodes for mobile devices who need the latest technical details and information on how to develop barcodes. It is also a useful reference for graduate students researching the field of barcode technology and mobile computing.

Automatic face location for videophone images

This paper presents a novel technique to automatically locate the face of a person in a videophone image. The proposed technique makes use of the intensity values of both luminance and chrominance components of the image. It detects face location by exploiting the distribution property of these components. The usefulness of face location information is also presented.

Foreground/background video coding using H.261

This research addresses the use of face segmentation to improve the subjective quality of videophone sequence encoded by the H.261-compliant coder. In this approach, each frame of the input video sequence is first segmented into two regions, namely, foreground and background. These regions are then encoded using the same coder but with different rate control and quantization level. In this way, the image quality of the more important foreground region can be improved by encoding it with more bits at the expense of background image quality. In this paper, we present a summary of the face segmentation technique required by this approach and then describe the implementation of this foreground/background (FB) coding scheme on the H.261 framework. The discriminatory quantization process and a new rate control strategy for the FB regions are also discussed. In addition, the performance of the FB coding scheme was evaluated by some experimental result carried out on the typical videophone sequences.

A performance study on MPEG-4 coder

This paper presents a performance study on MPEG-4 coder in videotelephony applications. This study addresses both MPEG-4 frame-based and object-based approaches to encoding videophone image sequences. The overhead cost, bit/quality transfer capability among video objects, and the use of video objects that are defined at different image resolutions are investigated.

Barcodes for Mobile Devices: Index

From inventory management in stores to automotive part tracking in assembly plants, barcodes are one of the most prevalent automatic identification and data capture technologies. This book provides a complete introduction to barcodes for mobile devices, presenting the most relevant and up-to-date information previously unavailable elsewhere or difficult to obtain. The focus throughout is on recent developments and two-dimensional (2D) barcodes, including the research and development steps towards colour barcodes for mobile devices, helping readers to develop their own barcodes. The authors also provide design details for their own novel colour 2D barcode: the Mobile MultiColour Composite (MMCC) barcode, plus coverage of RFID technology and one-dimensional barcodes. This book is ideal for professional developers of barcodes for mobile devices who need the latest technical details and information on how to develop barcodes. It is also a useful reference for graduate students researching the field of barcode technology and mobile computing.

Barcodes for Mobile Devices: Frontmatter

From inventory management in stores to automotive part tracking in assembly plants, barcodes are one of the most prevalent automatic identification and data capture technologies. This book provides a complete introduction to barcodes for mobile devices, presenting the most relevant and up-to-date information previously unavailable elsewhere or difficult to obtain. The focus throughout is on recent developments and two-dimensional (2D) barcodes, including the research and development steps towards colour barcodes for mobile devices, helping readers to develop their own barcodes. The authors also provide design details for their own novel colour 2D barcode: the Mobile MultiColour Composite (MMCC) barcode, plus coverage of RFID technology and one-dimensional barcodes. This book is ideal for professional developers of barcodes for mobile devices who need the latest technical details and information on how to develop barcodes. It is also a useful reference for graduate students researching the field of barcode technology and mobile computing.