Browsing by Author "Weng, Ping-Kuo"

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A Modified H.264 Intra-frame Video Encoder for Capsule Endoscope
(2008-01-01)
Dung, Lan-Rong
;
Wu, Yin-Yi
;
Lai, Hsin-Cheng
;
Weng, Ping-Kuo
;
電控工程研究所
The objective of this paper is to develop an ultra-low-power video compression processor for capsule endoscope to lower the RF transmitter bandwidth. In applications of capsule endoscope, it is imperative to consider battery life and performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much power from battery. There are also many fast video compression algorithms for reducing computation load; however, they may result in distortion of original image. A new video compression algorithm for gastrointestinal image based on H.264 Intra-frame encoder and its corresponding VLSI architecture are both proposed for low-power, high bite-rate wireless capsule endoscope. The algorithm exploits the characteristic of gastrointestinal image and H.264 intra-frame prediction technique to reduce computing complexity and save battery power consumption. As the result of implementation, the developed video compressor for 512-by-512 image sensor and 2 Mbits/sec RF transmitter costs 60k gates and consumes 0.9161mW power at 2 frames/sec while the average compression rate can be as low as 82%.
A Modified H.264 Intra-frame Video Encoder for Capsule Endoscope
(2008)
Dung, Lan-Rong
;
Wu, Yin-Yi
;
Lai, Hsin-Cheng
;
Weng, Ping-Kuo
;
電控工程研究所
The objective of this paper is to develop an ultra-low-power video compression processor for capsule endoscope to lower the RF transmitter bandwidth. In applications of capsule endoscope, it is imperative to consider battery life and performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much power from battery. There are also many fast video compression algorithms for reducing computation load; however, they may result in distortion of original image. A new video compression algorithm for gastrointestinal image based on H.264 Intra-frame encoder and its corresponding VLSI architecture are both proposed for low-power, high bite-rate wireless capsule endoscope. The algorithm exploits the characteristic of gastrointestinal image and H.264 intra-frame prediction technique to reduce computing complexity and save battery power consumption. As the result of implementation, the developed video compressor for 512-by-512 image sensor and 2 Mbits/sec RF transmitter costs 60k gates and consumes 0.9161mW power at 2 frames/sec while the average compression rate can be as low as 82%.
A Modified H.264 Intra-frame Video Encoder for Capsule Endoscope
(2008)
Dung, Lan-Rong
;
Wu, Yin-Yi
;
Lai, Hsin-Cheng
;
Weng, Ping-Kuo
;
電控工程研究所
The objective of this paper is to develop an ultra-low-power video compression processor for capsule endoscope to lower the RF transmitter bandwidth. In applications of capsule endoscope, it is imperative to consider battery life and performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much power from battery. There are also many fast video compression algorithms for reducing computation load; however, they may result in distortion of original image. A new video compression algorithm for gastrointestinal image based on H.264 Intra-frame encoder and its corresponding VLSI architecture are both proposed for low-power, high bite-rate wireless capsule endoscope. The algorithm exploits the characteristic of gastrointestinal image and H.264 intra-frame prediction technique to reduce computing complexity and save battery power consumption. As the result of implementation, the developed video compressor for 512-by-512 image sensor and 2 Mbits/sec RF transmitter costs 60k gates and consumes 0.9161mW power at 2 frames/sec while the average compression rate can be as low as 82%.
A Wireless Narrow-Band Imaging Chip for Capsule Endoscope
(2009)
Dung, Lan-Rong
;
Wu, Yin-Yi
;
Weng, Ping-Kuo
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
NBI endoscope has been shown to be a superior diagnostic tool for early stage lesion detection, equally wireless capsule endoscope has been proven a effective means of gastrointestinal tract diagnosis. In this paper, we present the first narrow band imaging wireless capsule endoscope. The dedicated dual-mode COMS sensor can offer both white light and narrow band images. Implementation results show that the designated 512- by-512 CMOS sensor consumes only 2mA at 3V power supply. The average current of the NBI capsule with a 8Mbps RF transmitter is nearly 7 mA that can work for 6 to 8 hours with two 1.5V 80mA button batteries while the frame rate is 2 fps.
An ultra-low-power image compressor for capsule endoscope
(2006-02-25)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
Weng, Ping-Kuo
;
電控工程研究所
;
Institute of Electrical and Control Engineering
Background: Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam. Methods: We developed an ultra-low-power image compression processor for capsule endoscope or swallowable imaging capsules. In applications of capsule endoscopy, it is imperative to consider battery life/performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much battery power. There are many fast compression algorithms for reducing computation load; however, they may result in distortion of the original image, which is not good for use in the medical care. Thus, this paper will first simplify traditional video compression algorithms and propose a scalable compression architecture. Conclusion: As the result, the developed video compressor only costs 31 K gates at 2 frames per second, consumes 14.92 mW, and reduces the video size by 75% at least.
GaSb/GaAs quantum dots and rings grown under periodical growth mode by using molecular beam epitaxy
(2015-09-01)
Chen, Hsuan-An
;
Shih, Tung-Chuan
;
Tang, Shiang-Feng
;
Weng, Ping-Kuo
;
Gau, Yau-Tang
GaSb/GaAs quantum dots (QDs) and quantum rings (QRs) are investigated. By using periodical growth interrupts, precise coverage control can be achieved for GaSb QD growth by using a single Ga source. With direct As irradiation to the substrate surface during the post soaking time, the soaking time can be effectively reduced while full ring morphologies and room-temperature QR luminescence can still be obtained by using this method. (C) 2015 Elsevier B.V. All rights reserved.
Image stitching and image reconstruction of intestines captured using radial imaging capsule endoscope
(2012-05-01)
Mang Ou-Yang
;
Jeng, Wei-De
;
Wu, Yin-Yi
;
Dung, Lan-Rong
;
Wu, Hsien-Ming
This study investigates image processing using the radial imaging capsule endoscope (RICE) system. First, an experimental environment is established in which a simulated object has a shape that is similar to a cylinder, such that a triaxial platform can be used to push the RICE into the sample and capture radial images. Then four algorithms (mean absolute error, mean square error, Pearson correlation coefficient, and deformation processing) are used to stitch the images together. The Pearson correlation coefficient method is the most effective algorithm because it yields the highest peak signal-to-noise ratio, higher than 80.69 compared to the original image. Furthermore, a living animal experiment is carried out. Finally, the Pearson correlation coefficient method and vector deformation processing are used to stitch the images that were captured in the living animal experiment. This method is very attractive because unlike the other methods, in which two lenses are required to reconstruct the geometrical image, RICE uses only one lens and one mirror. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.5.057004]