Informatics Publishing Limited

T. Thivya ¹, S. Jeeva ², S. Seedhanadevi ¹, T. Vithya ³

Affiliations
1 Sri Vidya College of Engineering & Technology, Virudhunagar, IN
2 Renganayagi Varatharaj College of Engineering, Sivakasi, IN
3 Mepco Schlenk Engineering College, Sivakasi, IN

Abstract

Enhancement of low contrast medical images is important for diagnosis of diseases. This paper presents a new approach for image enhancement using Shearlet Transform (ST). Enhancement includes increasing the contrast of the image and edge enhancement. The algorithm is based on modification of Shearlet coefficients by point-wise processing and reconstructing the modified coefficients. For further improvement of the processed image, the enhanced image is followed by adaptive histogram equalization. ST can fully capture the directional and other geometrical features at various scales and directions. In addition, it is highly effective in detecting both location and orientation of the edges, hence enhancement using ST provide good results. Ultrasound, mammogram and retinal images were examined. The proposed ST is compared with Contourlet and Wavelet Transform in terms of Entropy and is observed that the proposed method shows better enhancement of images.

Keywords

Shearlet Transform, Low Contrast Medical Image, Enhancement.

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R. Ganesan ¹, S. Pradeep ¹, R. Sinthuja ¹, T. Vithya ¹

Affiliations
1 Bharathiyar College of Engineering & Technology, Karaikal, U.T. of Puducherry, IN

Abstract

Existing traffic control system is using sensors. As the sensor which collects traffic flow information, mainly Ultrasonic Vehicle Detector has been used. This detector detects vehicle presence by the time difference of the reflection of ultrasonic wave fired from above the road surface to just under it. But especially queue and delay length are measured indirectly by the number of passed vehicles in a unit time. So a sensor which can collect more precise traffic flow information is needed. Also each Ultrasonic Vehicle Detector has to be installed above the road surface per a measurement lane and so there is a fear of spoiling the beauty of the city. On the other hand, the Digital Image processes an image received from the CCTV camera installed aside and above the approach lane at the traffic signal intersection. In this, queue length will be detected. To detect and measure queue parameters, two different algorithms have been used. The first algorithm is motion detection and the second is a vehicle detection operation. In this process, we detect moving vehicle grouping and delay vehicle grouping from the results of Image Preprocess, and calculate the delay range. Also, we make a stable output which is strong in the noise by smoothing the calculated delay range by referring to the output at the time of back and forth. After the queue length detection, depend upon the vehicles in four sides the preference will give to the vehicles. This saves the time and reduces the error in the existing system.

Keywords

Ultrasonic Vehicle Detector, Motion Detection, Vehicle Detection, Queue Length Parameters.

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