Digital Image Processing

Poonam Bhayan ¹, Gagandeep Jindal ²

Affiliations
1 Computer Science & Engineering at Chandigarh Engineering College, IN
2 Department of Computer Science & Engineering, Chandigarh Engineering College Landran, IN

Abstract

Image processing is one of most growing research area these days and now it is very much integrated with the medical and biotechnology field. Image Processing can be used to analyze different medical and MRI images to get the abnormality in the image. This abnormality can be described in terms of tumor or the patch or scare on the human body. We are presenting such an approach to detect the tumor from the lung image. In this proposed approach we have applied a series of operations, first to enhance the image and then to detect the tumor from the lung image. In this proposed approach, First of all some image enhancement and noise reduction techniques are used to enhance the image quality, after that we have applied watershed segmentation and some morphological operations to get the desired result. The algorithm has been tried on a number of different images from different angles and has always given the correct desired output.

Keywords

Contrast Stretching, Gabor Filter, Histogram Modeling, Morphological operations, Watershed Segmentation.

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Poonam Bhayan ¹, Gagandeep Jindal ²

Affiliations
1 Computer Science & Engg. at Chandigarh Engg. College, Landran, Mohali, IN
2 Department of Computer Science & Engineering at Chandigarh Engineering. College, Landran, Mohali, IN

Abstract

The paper describes very efficient method for processing lungs images for detection of abnormality in images. The result of image shows the portion containing abnormality. The process combines various methods for image enhancement including histogram equalization, gabor and fast fourier transform for improving quality of image to optimize the result of segmentation to best configuration. The process further combines morphological functions including tophat, bottomhat and watershed segmentation to effectively separate the region of interest to detect abnormality in image. Finally the portion marked by segmentation is extracted using masking and binary thresholding to obtain the abnormal features from images.

Keywords

Bottom Hat Function, Fast Fourier Transform, Gabor Filter, Histogram Equalization, Masking, Morphological Function, Top Hat Function, Watershed Segmentation.

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