The traditional analytical biosensor instruments are relatively bulky, expensive, and not easy to handle, thus their applications are largely limited in resource-limited settings. The recent development of microfluidic lab-on-a-chip (LOC) technology has provided a possible solution to miniaturize the conventional biosensing system, yet other accessory devices to detect, readout, analyze, transfer, and display results are still required. With the rapid development, mass production, and pervasive distribution of smartphones in recent years, they have provided people with portable, cost-effective, and easy-to-operate platforms to build analytical biosensors for point-of-care (POC) applications and mobile health. Based on the common analytical methods, this paper reviews the recent development of four types of smartphone based analytical biosensory systems at the POC, i.e., smartphone-based microscopic imaging, colorimetric, electrochemical, and electrochemiluminescence biosensor. The different bio-sensing strategies and analytical performance together with future perspectives are discussed.

Smartphone-based analytical biosensors

Automatic white balance is an important function of digital still cameras. The goal of white balance is to adjust the image such that it looks as if it is taken under canonical light. We proposed a novel technique to detect reference white points in an image. Our algorithm uses dynamic threshold for white point detection and is more flexible than other existing ad hoc algorithms. We have tested the algorithm on 50 images taken under various light sources. The results show that the algorithm is superior or comparable to other methods in both objective and subjective evaluations. The complexity of the algorithm is quite low, which makes it attractive for real-world applications.

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A novel automatic white balance method for digital still cameras

A robust automatic white balance algorithm is proposed in this paper, using extracting gray color points in images for color temperature estimation. A gray color point is the point where R, G and B components are equivalent under the canonical light source. A little color deviation of the gray color point from gray under different color temperature is used to estimate the color temperature of the light source. The test results show that the proposed algorithm can provide a good perceive effect and has the advantage of easy realization, low complexity and robust convergence.

Robust automatic white balance algorithm using gray color points in images

This paper presents an advanced video camera system which has robust automatic focus (AF), automatic exposure (AE), and automatic white-balance (AWB) control. The proposed AF algorithm decides the correct moving direction of the lens and detects the accurate in-focus state even though the scene is interfered with by the high light intensity. Experimental results demonstrate that the proposed system can be an effective alternative to conventional systems using the hill-climbing method.

An advanced video camera system with robust AF, AE, and AWB control

Underwater image restoration, which is the keystone to the underwater vision research, is still a challenging work. The key point of underwater image restoration work is how to remove the turbidity and the color distortion caused by the underwater environment. In this paper, we propose an underwater image restoration method based on transferring an underwater style image into a recovered style using Multi-Scale Cycle Generative Adversarial Network (MCycle GAN) System. We include a Structural Similarity Index Measure loss (SSIM loss), which can provide more flexibility to model the detail structural to improve the image restoration performance. We use dark channel prior (DCP) algorithm to get the transmission map of an image and design an adaptive SSIM loss to improve underwater image quality. We input this information into the network for multi-scale calculation on the images, which achieves the combination of DCP algorithm and Cycle-Consistent Adversarial Networks (CycleGAN). By compared the quantitative and qualitative with existing state-of-the-art approaches, our method shows a pleasing performance on the underwater image dataset.

Multi-scale adversarial network for underwater image restoration

A new algorithm of automatic white balance for electronic images has been developed. This algorithm uses fuzzy logic rules for determination of the color parameters in order to minimize the color temperature difference of various light sources. This algorithm has been implemented in a newly designed electronic still camera, and resulted in highly improved image quality. >

/pdf/automatic-white-balance-for-digital-still-camera-4knh7yb4y4.pdf

Automatic white balance for digital still camera

A new algorithm of automatic white balance for electronic images has been developed. This algorithm uses hzzy logic rules for determinationi of the color parameters in order to minimize the color temperature difference of various light sources. This algorithm has been implemented in a newly designed electronic still camera, and resulted in highly improved image quality.

http://ieeexplore.ieee.org/iel3/3916/11346/00517893.pdf

Ye-Quang Chen

Papers

Automatic white balance for digital still camera

Automatic white balance of digital still camera