Derivation of Optimal Global Equalization Function with Variable Size Block Based Local Contrast Enhancement

因为图象质量和对比改进是图象特征 largely.And 上的 depndent ，常规全球对比改进是困难的在各种各样的图象适用本地对比改进不仅引起褪色的效果，而且 blocks.To 解决这些缺点，这份报纸与可变尺寸块导出最佳的全球均等功能最佳的均等功能使它成为的基于的本地对比 enhancement.The

Image-based Water Level Measurement Method under Stained Ruler

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.

Night Vehicle Detection Using Variable Haar-Like Feature

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.

Real-Time Front Vehicle Detection Algorithm Based on Local Feature Tracking Method

This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of the vehicle are vertical and horizontal edges,shadow and symmetry.By comparing local features using the fixed window size,the features in the continuous images are tracked.A robust and fast Haarlike mask is used for detecting vertical and horizontal edges,and shadow is extracted by histogram equalization,and the sliding window method is used to compare both side templates of the detected candidates for extracting symmetry.The features for tracking are vertical edges,and histogram is used to compare location of the peak and magnitude of the edges.The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image,and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown.And it can be performed on real-time through applying it to the embedded system.

Vehicle Detection Method with Sub-stretching Based on Light Contrast in Fog Road Image

In this paper,detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image.Because of the fog in the image,a shape of an object is vague.Therefore an obstacle may occur on the vehicle detection.Thus,features from a foggy road image are surveyed through experiments,and a histogram is calculated with the bright value.The stretching method is then applied with the specific weight as the centre to detect a vehicle smoothly.If the high density area,from the view point of histogram,is applied with the stretching method,the definition of the image can be increased.On this fact,this paper proposed a method to divide the histogram and to determine applicable range of the stretching method.The improved results by the proposed methods are proved with the comparison tests between the proposed and previous methods.

Vehicle Detection in Still Images by Using Boosted Local Feature Detector

Vehicle detection in still images is a comparatively difficult task.This paper presents a method for this task by using boosted local pattern detector constructed from two local features including Haar-like and oriented gradient features.The whole process is composed of three stages.In the first stage,local appearance features of vehicles and non-vehicle objects are extracted.Haar-like and oriented gradient features are extracted separately in this stage as local features.In the second stage,Adaboost algorithm is used to select the most discriminative features as weak detectors from the two local feature sets,and a strong local pattern detector is built by the weighted combination of these selected weak detectors.Finally,vehicle detection can be performed in still images by using the boosted strong local feature detector.Experiment results show that the local pattern detector constructed in this way combines the advantages of Haar-like and oriented gradient features,and can achieve better detection results than the detector by using single Haar-like features.

Area Variation Based Color Snake Algorithm for Moving Object Tracking

一个蛇算法被知道了它在提取它是的 object.But 的准确轮廓有一个长处恰当在 2D 图象的一个动人的对象的形状改变非常到期的 ta 被散布的边在控制 points.Since 附近影响它在 3D 空格的旋转和翻译，考虑慢慢地动人的对象的常规算法不能提供适当 solution.To 当最小化缺点时，利用蛇 algrithm 的优点，这份报纸建议

Facial Expression Recognition by Split Rectangle Based Adaboost

The facial expression recognition system using the Adaboost based on the Split Rectangle feature is proposed in this paper.This system provides more various features in increasing speed and accuracy than the Haar-like feature of Viola,which is commonly used for the Adaboost training algorithm.The Split Rectangle feature uses the mask-like shape composed with 2 independent rectangles,instead of using mask-like shape of Haar-like feature,which is composed of 2～4 adhered rectangles of Viola.Split Rectangle feature has less diverged operation than the Haar-like feature.It also requires less operation because the sum of pixels requires only two rectangles.Split Rectangle feature provides various and fast features to the Adaboost,which produces the strong classifier with increased accuracy and speed.In the experiment,the system had 5.92 ms performance speed and 84%～94% accuracy by learning 5 facial expressions,neutral,happiness,sadness,anger and surprise with the use of the Adaboost based on the Split Rectangle feature.