This paper proposes the water level measuring method based on the image,while the ruler used to indicate the water level is stained.The contamination of the ruler weakens or eliminates many features which are required...This paper proposes the water level measuring method based on the image,while the ruler used to indicate the water level is stained.The contamination of the ruler weakens or eliminates many features which are required for the image processing.However,the feature of the color difference between the ruler and the water surface are firmer on the environmental change compare to the other features.As the color differences are embossed,only the region of the ruler is limited to eliminate the noise,and the average image is produced by using several continuous frames.A histogram is then produced based on the height axis of the produced intensity average image.Local peaks and local valleys are detected,and the section between the peak and valley which have the greatest change is looked for.The valley point at this very moment is used to detect the water level.The detected water level is then converted to the actual water level by using the mapping table.The proposed method is compared to the ultrasonic based method to evaluate its accuracy and efficiency on the various contaminated environments.展开更多
This paper proposes a night-time vehicle detection method using variable Haar-like feature.The specific features of front vehicle cannot be obtained in road image at night-time because of light reflection and ambient ...This paper proposes a night-time vehicle detection method using variable Haar-like feature.The specific features of front vehicle cannot be obtained in road image at night-time because of light reflection and ambient light,and it is also difficult to define optimal brightness and color of rear lamp according to road conditions.In comparison,the difference of vehicle region and road surface is more robust for road illumination environment.Thus,we select the candidates of vehicles by analysing the difference,and verify the candidates using those brightness and complexity to detect vehicle correctly.The feature of brightness difference is detected using variable horizontal Haar-like mask according to vehicle size in the location of image.And the region occurring rapid change is selected as the candidate.The proposed method is evaluated by testing on the various real road conditions.展开更多
基金supported by the Brain Korea 21 Project in 2010,the MKE(The Ministry of Knowledge Economy,Korea)the ITRC(Information Technology Research Center)support program(NIPA-2010-(C1090-1021-0010))
文摘This paper proposes the water level measuring method based on the image,while the ruler used to indicate the water level is stained.The contamination of the ruler weakens or eliminates many features which are required for the image processing.However,the feature of the color difference between the ruler and the water surface are firmer on the environmental change compare to the other features.As the color differences are embossed,only the region of the ruler is limited to eliminate the noise,and the average image is produced by using several continuous frames.A histogram is then produced based on the height axis of the produced intensity average image.Local peaks and local valleys are detected,and the section between the peak and valley which have the greatest change is looked for.The valley point at this very moment is used to detect the water level.The detected water level is then converted to the actual water level by using the mapping table.The proposed method is compared to the ultrasonic based method to evaluate its accuracy and efficiency on the various contaminated environments.
基金supported by the MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)by the Brain Korea 21 Project in2011
文摘This paper proposes a night-time vehicle detection method using variable Haar-like feature.The specific features of front vehicle cannot be obtained in road image at night-time because of light reflection and ambient light,and it is also difficult to define optimal brightness and color of rear lamp according to road conditions.In comparison,the difference of vehicle region and road surface is more robust for road illumination environment.Thus,we select the candidates of vehicles by analysing the difference,and verify the candidates using those brightness and complexity to detect vehicle correctly.The feature of brightness difference is detected using variable horizontal Haar-like mask according to vehicle size in the location of image.And the region occurring rapid change is selected as the candidate.The proposed method is evaluated by testing on the various real road conditions.
