Evaluation of Dense Fog to Assess the Road Condition using Backscattered Veil Approach

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International Journal of Electrical, Electronics and Computer Systems (IJEECS)

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ISSN (Online): 2347-2820, Volume -4, Issue-8, 2016 57

Evaluation of Dense Fog to Assess the Road Condition using Backscattered Veil Approach

1Sahana V, ²Usha K Patil, ³Syed Thouheed Ahmed

1,2Computer Science & Engineering, GSSSIETW, Mysuru, Karnataka

3HR & Sr. Research Engineer, ThinkSoft Research &Information Technologies, Bengaluru

Abstract:Camera based driver help frameworks are progressively utilized as a part of flow vehicles. Surely understood applications are for instance the Lane Departure Warning, the Speed Limit Information, the High Beam Assistant or the Adaptive Cruise Control.

Every one of these applications have in like manner that they perceive particular items in the picture like paths, movement signs, lights or vehicles. In any case, a perceiving general picture property, for example, current climate conditions, has so far.This paper is proposing the technique of fog detection under the given scenario of back-veil scattering technique. This paper presents the overall scenario of detecting and analyzing the given input video is acquired and processed for fast processing and the expected results are discussed in this paper. The system is efficient in understanding and analyzing the visibility intensity and obstacle detection.

Keywords: Fog Characterization, Fog Detection, Visibility.

I. INTRODUCTION

Fog is an obvious mass comprising of cloud water beads or ice gems suspended noticeable all around at or close to the Earth's surface. Fog can be viewed as a kind of low-lying cloud and is vigorously impacted by close-by waterways, geography and wind conditions. Thusly mist has influenced numerous human exercises, for example, transportation, travel and fighting. The expression "Fog"

is ordinarily recognized from the bland term "cloud" in the haze is low-lying and the dampness in the haze is frequently produced locally, for example, adjacent waterway, similar to a lake or sea, or from close-by sodden ground or bogs. By definition, haze diminishes perceivability to under 1 kilometer, while fog causes lesser disability of perceivability

Different vehicle impact is especially destructive as the mass of folded vehicles makes escapes for survivors troublesome. Regardless of the fact that survivors can leave their vehicles, different autos may strike them.

Separately vehicles in a various vehicle crash are regularly hit numerous times at rapid, expanding the danger of harm to travelers who may have survived the principal sway with the advantages of now released defensive airbags. Impact after the underlying crash may happen from the side of the vehicle, where the travelers' compartment is more powerless.

The obliteration and extreme warmth may harm the roadways, especially by softening and smoldering the black-top or spelling solid surfaces. The auxiliary steel of extensions and bridges can likewise be debilitated by the warmth. A blazing accident inside a passage is the most genuine, as they is little intends to get away from the toxic vapor, and the kept warmth may harm basic backings. The expansive size of these mishaps can close essential roadway courses for a few days, or considerably more if parkways bolster structures are harmed.

They are broadly utilized as a part of the petroleum and petrochemical businesses, for the most part to accomplish exceptionally fast gas spill recognition for combustible gasses focuses similar to the lower combustible breaking point. They are additionally utilized however so far to a lesser degree, in different businesses where combustible focus can happen, for example, in coal mining and water treatment. On a fundamental level the method can likewise be utilized to identify dangerous gasses, for occasion hydrogen sulfide, at the vital parts per million focuses, yet the specialized troubles included have so far averted far reaching selection for lethal gasses.

II. SYSTEM DESIGN

Framework engineering is to be considered as a center of configuration as it comprises of major contributing modules and framework is future separated into modules for execution under these situations. A brief framework design is showcased in the Figure 1. It comprises of information video module with highlight extraction and picture layer disintegration module. Each is autonomously dissected and brought for preparing under layer improvement lastly we have a handling unit for location of fog picture.

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Figure 1: System Architecture

Framework back scattered separation examination strategy is utilized as shown in the figure 2 to perceive the Fog nearness in our proposed framework. The method is utilized to examinations pictures at a haloids perspective and in this way processes the general framework effectiveness proportion of performing a choice of fog nearness and nonattendance.

Figure 2: Diverse impacts of fog on light engendering in a driving scene.

Another wonder that adds to the loss of differentiation in the scene is connected to back-dissipating as shown in the figure 3. Albeit the vast majority of the vitality is scattered forward, some is scattered in reverse toward the driver, producing a changeless veiling impact before the auto.

Figure 3: Back-Scattered Veil Detection Proposed System

The figure 4 portrays the connection between the processor and the leader where in the underlying stage the camera gets the video or the still pictures if the climate if foggy. Once the video is obtained by the camera it will taken for the pre handling in the wake of

preprocessing the video will be separated into edges and stores in the .JPG organize and sends back to the information tests, the casings will be put away in the cushion and thee test of every edge will be brought from the cradle and take it for the discovery procedure in the event that it is certain then the casing ID will goes to information tests, that edge ID will be send to basic leadership for applying the backscattered strategy then bringing the limit esteem from that edge for the basic leadership that the haze is available or not if the outcome is sure then that casing will be taken and sends to the driver for the assessment of the street condition.

Figure 4: General Framework Design

Figure 5: Module Feature Extraction

As ROI is acquired in the figure 5, the components are extricated in early state under a crude area of examination. Local Location solidifying and diffuse example of Fog is dissected under example examination unit. On coordinating with past picture outline, the framework is migrated to perceive the past example and procedure towards basic leadership. Else the framework experiences new examples and gives an intense quality examination of new examples.

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Figure 6: Decision Making Unit

Framework back scattered separation investigation method is utilized to perceive the Fog nearness in the proposed framework. The strategy is utilized to investigations pictures at a haloid perspective and accordingly processes the general framework productivity proportion of performing a choice of fog nearness and nonappearance as appeared in the figure 6.

Experimental Results

The proposed system is detecting the fog intensities in the figure 7 and thus escalating the overall system performance and thus the system is seen with detection ratio under visibility and obstacle detection.

Figure 7: Fog Intensity Values

The layer examination will be fulfilled once the edges are fragmented. At the point when the layer upgrade is finished by utilizing the Region of Interest, the locale where the thick haze is available will be stop which is as appeared in the figure 8. The investigated layer and the picture will changed over into highly contrasting for the identification of the thick fog. In the figure the white shading shows the identification of the thick fog.

Figure 8: Detection of Thick Fog

III. CONCLUSION

The proposed system is designed and programmed for automobile application in detection of fog and thus retrieve a decision on performance and its overall behavior. In this system, data preprocessing and unique ID framing is achieved to gain higher range of data mobility and thus generalized frames are obtained. The system is also featured with ROI detection and pattern extraction under normal and hypostatical state of video frames.

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