Background: Radiography plays an important role in medical image processing. At present, different radiographic techniques such as X-ray, Computer Topography (CT), and Magnetic Resonance Imagining (MRI) are commonly used in the field of pediatric health informatics. These techniques are used to analyze the anatomical structures and other regions of the human body. In nature, radiography image contains a lot of noise, irrelevant information, intensity problems and partial volume effect which makes the task of locating and analyzing the suspicious area in such a image is very difficult task. Methods: Existing works does not focus more on segmentation corresponding to the aspired foreign body pediatric radiography images. Therefore, this work analyzed eleven image segmentation techniques are discussed in [Table 3] and proposed a hybrid segmentation technique with the combination of Median filtering, Iterative thresholding and K-means clustering which is named as MIK segmentation technique. Results: The quantitative metrics such as SNR, PSNR, RMSE and MAE are computed for evaluating the performance of segmentation techniques. Conclusions: The performance evaluation results prove that the proposed MIK segmentation technique is the most suitable segmentation technique for foreign body aspired pediatric radiography images. © 2016, Institute of Integrative Omics and Applied Biotechnology. All rights reserved.