No-Reference Quality Assessment of the Gaussian Blur Image Depending on Local Standard Deviation

No-reference measurement of blurring artifacts in images isa difficult problem in image quality assessment field. In this paper, we present a no-reference blur metric to estimatethe quality of theimages. These images are degraded using Gaussian blurring. Suggestion method depends on developing the Mean of Locally Standard deviation this method is called Blur Quality Metric (BQM) and itcalculatesby using gamma correction and reblurring the image again And the BQM is compared with the No-reference Perceptual Blur Metrics (PBM)and the Entropy of the First Derivative (EFD) Image; the BQM is a simple metric and gives good accuracy in metrics the quality for theGaussian blurred image if it compared with another algorithms. The BQM satisfied high correlation coffecion compared with another method. Keywords: No-referencequality assessment, Gaussian blurring, Standard deviation, mean

Contrast Enhancement of Brightness-Distorted Images by Improved Adaptive Gamma Correction

As an efficient image contrast enhancement (CE) tool, adaptive gamma correction (AGC) was previously proposed by relating gamma parameter with cumulative distribution function (CDF) of the pixel gray levels within an image. ACG deals well with most dimmed images, but fails for globally bright images and the dimmed images with local bright regions. Such two categories of brightness-distorted images are universal in real scenarios, such as improper exposure and white object regions. In order to attenuate such deficiencies, here we propose an improved AGC algorithm. The novel strategy of negative images is used to realize CE of the bright images, and the gamma correction modulated by truncated CDF is employed to enhance the dimmed ones. As such, local over-enhancement and structure distortion can be alleviated. Both qualitative and quantitative experimental results show that our proposed method yields consistently good CE results

Target recognitions in multiple camera CCTV using colour constancy

People tracking using colour feature in crowded scene through CCTV network have been a popular and at the same time a very difficult topic in computer vision. It is mainly because of the difficulty for the acquisition of intrinsic signatures of targets from a single view of the scene. Many factors, such as variable illumination conditions and viewing angles, will induce illusive modification of intrinsic signatures of targets. The objective of this paper is to verify if colour constancy (CC) approach really helps people tracking in CCTV network system. We have testified a number of CC algorithms together with various colour descriptors, to assess the efficiencies of people recognitions from real multi-camera i-LIDS data set via Receiver Operating Characteristics (ROC). It is found that when CC is applied together with some form of colour restoration mechanisms such as colour transfer, the recognition performance can be improved by at least a factor of two. An elementary luminance based CC coupled with a pixel based colour transfer algorithm, together with experimental results are reported in the present paper

DIGITAL IMAGE ENHANCEMENT USING THE METHOD OF MULTISCALE RETINEX AND MEDIAN FILTER

At this time digital image used by a lot of people to capture the moment or other important things, digital image itself is the result of shooting with a digital camera, although today's digital cameras are already equipped with features that support the results of the picture, but not all digital image that is produced in accordance with our wishes, it happens because of a problem on the quality of the image, situation and condition at the time of the shooting process the image will affect on the quality of the image causes the image results to be bright or dark. Then from that needed improvement of the quality of the image so that the image that is produced in accordance with our wishes, in this study, the methods used in improving the quality of image is using the method of Multiscale Retinex and Median Filters. The process of Multiscale Retinex will produce the image of a more bright compared to the original image that minimal light intensity, while the Median filter will produce a clearer image because it can reduce the noise/noise in the image, the parameters used in this study is Histogram of some data that has been researched histogram chart shows the value of the intensity of the pixel average is close to zero (0) after processed by the method of Multiscale Retinex and the Median Fiter value of the intensity of the pixel average show a change of the charts is approaching 250 which indicates an increase in the brightness of the digital image brighter

Development of Hand-cleaning Service-oriented Autonomous Navigation Robot

[[abstract]]This paper proposes the development of an autonomous navigation robot with hand-cleaning service in indoor environments. To navigate in unknown environments and provide service, the robot is with several intelligent behaviors including wall-following, obstacle avoidance, autonomous navigation, and human detection. A laser-sensor-based approach is used in the wall-following and obstacle avoidance behavior controllers. A preliminary map-matching algorithm is applied in the localization strategy of autonomous navigation in which the robot can acquire the current location and then move toward to the target position. In this study a hand-cleaning mechanism is embedded into the robot and the service will activate while a human is recognized within the designated range. The overall robotic system is carried out using a two-wheeled driving mobile robot with LabVIEW as an integration tool. The experimental results demonstrate the practicable application of the proposed approach.[[conferencetype]]國際[[conferencedate]]20121014~20121017[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Seoul, Kore

Automated, on-board terrain analysis for precision landings

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown

Retinex theory for color image enhancement: A systematic review

A short but comprehensive review of Retinex has been presented in this paper. Retinex theory aims to explain human color perception. In addition, its derivation on modifying the reflectance components has introduced effective approaches for images contrast enhancement. In this review, the classical theory of Retinex has been covered. Moreover, advance and improved techniques of Retinex, proposed in the literature, have been addressed. Strength and weakness aspects of each technique are discussed and compared. An optimum parameter is needed to be determined to define the image degradation level. Such parameter determination would help in quantifying the amount of adjustment in the Retinex theory. Thus, a robust framework to modify the reflectance component of the Retinex theory can be developed to enhance the overall quality of color images