Feature extraction and track measurement for low resolution images: A cost effective method

In a track counting system a digital USB CCD camera is often used to make a communication between the visually seen etched tracks of a solid state nuclear track detector and the image analyzer software installed on the PC. The camera's characteristics determine the size of the image, and the number of pixels per track. The resolution and contrast of the images are the key features in how well an image analyzer can perform the task of track measurement. In this paper we present an approach to increase the resolution and contrast of the images, aiming to extract the features which cannot be simply attained from the original image. The presented algorithm as an image processing technique is used to replace the economical cost of high quality imaging system with the computational cost of image processing. The tracks' characteristics will remain intact and the contrast of the image will be enhanced through Shannon entropy reaching its maximum. Feature preservation is done through maximizing the similarity between the original low resolution image and the processed higher resolution image. Similarity is defined as the mutual information between two images. This resolution increment will result in contrast enhancement and increased information transfer for feature extraction purpose. Experimental images of alpha tracks taken by a 350KP USB digital camera are used to verify the efficiency of the proposed algorithm.

► Two objectives, one for contrast enhancement and another for feature preservation. ► Quality improvement of low resolution nuclear track images. ► Replacing the cost of a high quality imaging system with computation cost. ► A Robust optimization method for problems of nuclear track images analysis. ► Achieving a method for more accurate accumulate dose measurements.