Journal of Pure and Applied Ultrasonics

G. R. Sinha ¹, Kavita Thakur ²

Affiliations
1 Department of Electronics & Telecom, Chhattisgarh Institute of Technology, Rajnandgaon, IN
2 Pt. Ravishankar Shukla University, Raipur, IN

Abstract

Images from an ordinary digital camera or scanner convey information at a wide range of spatial scales and enable the viewer to decompose the image into uniform regions that are some way to recognize familiar images, determine spatial relationships between images, and detect abnormalities. Medical image analysis poses a great challenge as the need for image filtering, because medical images have a poor SNR than scenes taken with a digital camera; the spatial resolution is often frustratingly low, the contrast between anatomically distinct structure is often too low to be computed reliably using a standard image processing technique. It is interesting to note that a great deal of image filtering takes place at what is usually regarded as a "pre-processing" stage in the formation of a medical image and is relatively invisible to a radiologist. However, there is an increasing awareness of the impact of post processing algorithms particularly filtering in diagnostic applications and an awareness of these types of techniques is useful. The present paper deals with a set of filtering" operations which enable the user to improve the image such as image smoothing of ultrasonic or x-ray images that removes noise at high frequencies, sharpening that increases high frequency content, contrast stretching etc. Such image filtering is designed to improve the appearance of an image, relying on the human visual system to disregard any unwanted change of content of the image. The filtering process facilitates the detection of suspicious and inhomogeneous areas thus improving the diagnostic confidence.

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Onkar Dixit ¹, G. R. Sinha ¹, Kavita Thakur ²

Affiliations
1 Chhattisgarh Institute of Technology, Rajnandgaon, IN
2 Pt. R.S.U., Raipur, IN

Abstract

This paper presents an effective approach to the detection of small objects by employing frequency transformation method. In this work, moving objects with small size and low contrast are first detected from an image sequence which was captured from an image from the database. The proposed detection system includes two main modules, region of interest locating and contour extraction. A novel neighboring encoding technique along with the image differencing technique is devised here to effectively reduce noise which usually affects the performance of detection results, especially for small objects. Next, we find the bounded rectangles enclosing the denoised images, which in turn generate region of interest. Experimental results validate that the proposed approach is indeed feasible and effective in detecting objects with small size and low contrast.

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