色彩熵在图像质量评价中的应用

目的 由于色彩空间包含了图像的大量信息,而且Lab色彩空间更接近于人眼视觉,因此提出一种改进的无参考图像质量评价算法IQALE(image quality assessment using Lab color space and entropy),通过在SSEQ(spatial-spectral entropy-based quality)算法中加入Lab色彩空间a通道和b通道的特征来提高算法精度。方法 信息熵是近几年研究较多的图像特征,并且能较好地运用在图像质量评价研究中。该文在色彩空间和灰度空间同时提取信息熵特征,通过支持向量机(SVM)对图像特征和MOS值进行训练和测试。结果 在LIVE、TID2008、MICT、CSIQ和IVC这5个常用数据库上的实验结果表明:在算法中加入Lab色彩空间信息可以提高算法精度,并且本文算法IQALE的效果优于目前流行的无参考图像质量评价算法。为了验证算法的可扩展性,该文还在这5个数据库上进行了数据库独立性实验。结论 从实验结果来看,本文提出的IQALE算法通过加入色彩熵特征使得算法具有较高且较稳定的精度,数据库独立性实验也体现了算法较好的鲁棒性,对于各种失真类型都具有较好的普适性。     

Shadow detection of moving objects based on multisource information in Internet of things

Abstract

Moving object detection is an important part in intelligent video surveillance under the banner of Internet of things. The detection of moving target’s shadow is also an important step in moving object detection. On the accuracy of shadow detection will affect the detection results of the object directly. Based on the variety of shadow detection method, we find that only using one feature can’t make the result of detection accurately. Then we present a new method for shadow detection which contains colour information, the invariance of optical and texture feature. Through the comprehensive analysis of the detecting results of three kinds of information, the shadow was effectively determined. It gets ideal effect in the experiment when combining advantages of various methods.     

An Accumulation Algorithm for Video Shot Boundary Detection

In this paper, an accumulation algorithm for video shot detection is introduced. The algorithm considers the properties of gradual transition. In a gradual transition, there is only a small difference between consecutive frames. The algorithm remembers the differences between consecutive frames and accumulates them. When the accumulation difference exceeds a threshold, an occurrence of shot transition is declared. Our main contributions are to introduce a frame C that remembers the changes from the beginning of a shot and detect the different types of boundaries (cut, fade, dissolve) at one process. We tested our algorithm with clips extracted from MPEG VCDs. The algorithm showed a good performance in detecting the gradual transitions as well as the abrupt cuts and has the ability to identify different types of boundaries.     

Real-time background generation and foreground object segmentation for high-definition colour video stream in FPGA device

The processing of a high-definition video stream in real-time is a challenging task for embedded systems. However, modern FPGA devices have both a high operating frequency and sufficient logic resources to be successfully used in these tasks. In this article, an advanced system that is able to generate and maintain a complex background model for a scene as well as segment the foreground for an HD colour video stream (1,920 × 1,080 @ 60 fps) in real-time is presented. The possible application ranges from video surveillance to machine vision systems. That is, in all cases, when information is needed about which objects are new or moving in the scene. Excellent results are obtained by using the CIE Lab colour space, advanced background representation as well as integrating information about lightness, colour and texture in the segmentation step. Finally, the complete system is implemented in a single high-end FPGA device.     

Implicit relative attribute enabled cross-modality hashing for face image-video retrieval

Face image-video retrieval refers to retrieving videos of a specific person with image query or searching face images of one person by using a video clip query. It has attracted much attention for broad applications like suspect tracking and identifying. This paper proposes a novel implicit relative attribute enabled cross-modality hashing (IRAH) method for large-scale face image-video retrieval. To cope with large-scale data, the proposed IRAH method facilitates fast cross-modality retrieval through embedding two entirely heterogeneous spaces, i.e., face images in Euclidean space and face videos on a Riemannian manifold, into a unified compact Hamming space. In order to resolve the semantic gap, IRAH maps the original low-level kernelized features to discriminative high-level implicit relative attributes. Therefore, the retrieval accuracy can be improved by leveraging both the label information across different modalities and the semantic structure obtained from the implicit relative attributes in each modality. To evaluate the proposed method, we conduct extensive experiments on two publicly available databases, i.e., the Big Bang Theory (BBT) and Buffy the Vampire Slayer (BVS). The experimental results demonstrate the superiority of the proposed method over different state-of-the-art cross-modality hashing methods. The performance gains are especially significant in the case that the hash code length is 8 bits, up to 12% improvements over the second best method among tested methods.

     

Rapid determination of soil organic matter content based on soil colour obtained by a digital camera

ABSTRACT

Soil organic matter (SOM) is an important component of soil and a significant criterion in determining the dynamics of soil quality. A rapid, low-cost method to measure SOM content is needed to support the development of precision agriculture. This article studied the quantitative relationship between SOM and soil colour using a digital camera, which is relatively inexpensive and easy to operate, as a portable tool for obtaining colour information of the soil surface. The results show that mixed samples with different soil particle sizes reduce the noise of the image and are more suitable than uniform soil samples for predicting the SOM. Among the three bands of red, green, and blue (RGB), the red band had the best correlation with SOM, and its reciprocal correlation coefficient (r) reached 0.75. The reciprocal regression model of the RGB colour model provided good prediction results for mixed soil samples, with a coefficient of determination (R²) of 0.76 and a root mean square error (RMSE) of 0.55, and the validation result had an excellent predictive ability (R²_val = 0.85 and RMSE_val = 0.53). The single-variation predictive model of CIELa*b* colour space model through transformation of the RGB colour space model performed well. The model built by colour intensity values had a strong stability and forecasting capacity. Thus, a digital camera can be used as an alternative tool to rapidly measure SOM.     

一种新的视频镜头分割算法

镜头是视频分析和索引的基础，但是自动的镜头分割，尤其是渐变切换的检测还是一个很有挑战性的课题。本文提出了一种利用直方图与模板匹配相结合来进行视频镜头切变检测的算法和一种利用图象灰度级平均(MGL)来进行渐变检测的算法，该渐变检测算法能有效区分摄象机镜头的运动和渐变。实际测试证明，利用本文算法进行视频镜头检测
能取得比较好的效果。     

Multiple scale-specific representations for improved human action recognition

Human action recognition in video is important in many computer vision applications such as automated surveillance. Human actions can be compactly encoded using a sparse set of local spatio-temporal salient features at different scales. The existing bottom-up methods construct a single dictionary of action primitives from the joint features of all scales and hence, a single action representation. This representation cannot fully exploit the complementary characteristics of the motions across different scales. To address this problem, we introduce the concept of learning multiple dictionaries of action primitives at different resolutions and consequently, multiple scale-specific representations for a given video sample. Using a decoupled fusion of multiple representations, we improved the human classification accuracy of realistic benchmark databases by about 5%$5\%$, compared with the state-of-the art methods.     

Detection of gradual transitions in video sequences using B-spline interpolation

We present a novel technique for detecting the presence of a gradual transition in video sequences and automatically identifying its type. Our scheme focuses on analyzing the characteristics of the underlying special edit effects and estimates actual transitions by polynomial data interpolation. In particular, a B-spline interpolation curve fitting technique is used. We make use of "goodness" of fitting to determine the presence of gradual transitions. Our approach is able to recover the original transition behavior of an edit effect even if it is distorted by various post-processing stages. Our gradual transition detectors have been extensively tested on various genres of real video sequences to evaluate the performance of the proposed algorithms.     

Normalization of satellite imagery

Abstract

Sets of Thematic Mapper (TM) imagery taken over the Washington DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal colour changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band colour imagery can be directly interpreted for quantitative information of the target.     

Colour Names as Response Criteria∗

Abstract

A study was conducted to determine the consistency of colour naming of chemical reaction spots among subjects and trained chemists. The following conclusions were drawn.

1. Single, arbitrarily assigned names are inadequate to convey unequivocal meaning to a group of observers who must base important decisions on their judgment of colour.

2. When it was logically possible to group a large number of names into one or two overall categories, observer agreement is markedly increased. 3. The study of such regrouped names together with the associated colours makes it possible to construct a colour continuum-bar which obviates the need for colour naming altogether, but facilitates direct comparison of spot colours with criterion colours.     

A common type of commercially available LED light source allows for colour discrimination performance at a level comparable to halogen lighting

Abstract

As light sources based on light emitting diodes (LED) are increasingly used to replace classic tungsten-based light sources in household lighting applications, possible impairments of colour perception under those light sources due to a different spectral power distribution become a major concern. The Colour Rendering Index (CRI) which is the only measure available to the end user is controversial and does not represent a comprehensive measure of colour perception. Aspects of colour perception disregarded by the CRI such as colour discrimination have to be taken into account as well. Therefore, we evaluated colour discrimination performance under a commercially available phosphor-converted LED light source from a popular brand (OSRAM) in comparison to a classic tungsten-based halogen light source. Colour discrimination performance was not affected by the type of light source, indicating that the phosphor-converted LED light source enables colour discrimination performance comparable to that of halogen lighting despite being associated with a lower CRI.

Practitioner summary: Considering the increasing use of energy efficient light sources, we compared colour discrimination under a common type of phosphor-converted LED and under traditional halogen lighting. Colour discrimination performance was comparable in both lighting conditions, indicating that the phosphor-converted LED can replace halogen lighting without sacrificing colour discrimination for energy efficiency.

Abbreviations: LED: light emitting diode; CRI: colour rendering index; CCT: correlated colour temperature; CIE: commission internationale de l’éclairage; FMHT: Farnsworth-Munsell 100-Hue Test; lm: lumen; lx: lux, lumen/m^2; W: watt; nm: nanometer; K: kelvin     

Novel Shot Boundary Detection in News Streams Based on Fuzzy Petri Nets

ABSTRACT

With the advent of a digital era, people have encountered some difficulty in using and absorbing overwhelming information generated by technological advances in multimedia. Thus, the development of video summarization enables people to catch a general idea about videos in a short time. In this paper, we focus on the shot change, a part of the video summarization, to conduct an experimental sample on news programs. Moreover, a high-level fuzzy Petri net model is presented to describe the frame combination which indicates a shot boundary used for a video frame sequence in order to detect both cut transitions and gradual transitions. This study has used feature functions to estimate the direct shot change in consideration of video shot boundary detection which adopts the HLFPN model to find a threshold value. The experimental results manifest that the proposed system saves a lot of time and reduces the occurrence of improper shot changes caused by the motions of objects and cameras when comparing the proposed approach with other existing ones.     

一种渐变镜头检测方法

镜头检测与分割在视频检索中起着关键的作用。切变镜头识别已有许多成熟的方法。如何识别渐变镜头是视频分割中的难点。文章利用视频中图像帧直方图方差的变化,提出了一种渐变镜头的分割方法。实验表明,该方法简单有效,且具有较高的精度。     

MusiCam: an instrument to demonstrate chromaphonic synesthesia

Abstract

Inspired by a type of synesthesia where colour typically induces musical notes the MusiCam project investigates this unusual condition, particularly the transition from colour to sound. MusiCam explores the potential benefits of this idiosyncrasy as a mode of human computer interaction (HCI), providing a host of meaningful applications spanning control, communication and composition. Colour data is interpreted by means of an off-the-shelf webcam, and music is generated in real-time through regular speakers. By making colour-based gestures users can actively control the parameters of sounds, compose melodies and motifs or mix multiple tracks on the fly. The system shows great potential as an interactive medium and as a musical controller. The trials conducted to date have produced encouraging results, and only hint at the new possibilities achievable by such a device.     

Do visual word segmentation cues improve reading performance in Chinese reading？

Abstract

It is controversial whether providing visual word segmentation cues can improve Chinese reading performance. This study investigated this topic by examining how visual word segmentation cues such as grey highlighting, red colour and interword spacing influence global sentence reading and local word recognition during reading Chinese text in three experiments. The results showed that interword spacing could facilitate local word recognition but could not increase reading speed. In contrast, grey highlighting and red colour could improve neither local word recognition nor global sentence reading performance. Instead, these cues increased the number of fixations and saccades, resulting in slower reading speed. These results suggest that even red colour is not a practically visual cue for Chinese word segmentation and the corresponding mechanisms were discussed.

Practitioner Summary: We studied how visual cues such as grey highlighting, red colour and interword spacing influenced Chinese reading performance. Our data showed that even the red colour was not an efficient cue for Chinese word segmentation. The corresponding mechanisms and future direction were discussed regarding how to improve Chinese reading performance.     

Neural Networks Based Colour Measuring for Process Monitoring and Control in Multicoloured Newspaper Printing

This paper presents a neural networks based method and a system for colour measurements on printed halftone multicoloured pictures and halftone multi-coloured bars in newspapers. The measured values, called a colour vector, are used by the operator controlling the printing process to make appropriate ink feed adjustments to compensate for colour deviations of the picture being measured from the desired print. By the colour vector concept, we mean the CMY or CMYK (cyan, magenta, yellow, and black) vector, which lives in the three- or four-dimensional space of printing inks. Two factors contribute to values of the vector components, namely the percentage of the area covered by cyan, magenta, yellow and black inks (tonal values) and ink densities. Values of the colour vector components increase if tonal values or ink densities rise, and vice versa. If some reference values of the colour vector components are set from a desired print, then after an appropriate calibration, the colour vector measured on an actual halftone multicoloured area directly shows how much the operator needs to raise or lower the cyan, magenta, yellow and black ink densities to compensate for colour deviation from the desired print. The 18 months experience of the use of the system in the printing shop witnesses its usefulness through the improved quality of multicoloured pictures, the reduced consumption of inks and, therefore, less severe problems of smearing and printing through.     

Video sequence feature extraction and segmentation using likelihood regression model

The development of digital technology is utilized by people to capture and share video frames. At present, rather than capturing images, people are interested in recording video footage for exploring information. Here, retrieval of video from large databases is challenging due to the continuous frame count. To overcome these challenges associated with the retrieval of video from available databases, this research proposed a likelihood-based regression approach for video processing. To improve the retrieval accuracy of video sequences, the proposed method utilizes a likelihood estimation technique integrated with a regression model. The likelihood estimate measures the pixel level roughly for estimating the pixel range, after which the regression approach measures the pixel level for transforming certainly blurred and unwanted pixels. In the proposed likelihood regression approach, the video is converted into a video frame and stored in a database. Query frames are taken into account by the generated database depending on the features which are used for a given video to be retrieved. The significant video retrieval performance obtained from the simulation results for the proposed likelihood-based regression model shows that the proposed model performs well over the other state-of-the-art techniques.

     

Visualization using colour: Visual presentation of events in particle physics

This paper applies a model of colour vision to achieve optimal use of colour in a software system that visualizes the results of experiments in high energy physics. It shows how the elements of the visualization were designed and provides details of why particular colours were chosen. By grounding these findings in psychological research, it is able to show how other computer systems that use colour may profitably apply this methodology.