Masters Theses

Keywords and Phrases

Border Detection; Dermoscopy; Focus Detection; Lesion Segmentation; Pill Shape Detection; Vision Based Measurements


“Vision-based applications are increasing with the increase in technology and are making a huge impact in this global civilization. A vision-based measurement approach for pill shape detection was developed for medical pill identification, a focus detection method was developed for digital dermoscopy, and a machine learning approach was used for automatic lesion segmentation, which assists in automatic melanoma diagnosis. Rapid and accurate pill identification is needed by medical and law enforcement personnel during emergencies. But, one of the main parameters in pill identification is the shape of the pill. An Adaptable-Ring approach describes a novel technique to accurately detect the complex pharmaceutical pill shapes using measurements derived from a superimposed adaptable ring. It is shown that these measurements suffice to successfully classify the shapes of the pills currently in the Pillbox database (U.S. National Library of Medicine, 2014). Though developed for the domain of pharmaceutical pill shapes, this method can be applied to other industrial applications. Identification of an unfocused image is essential during automatic diagnosis of melanomas because, when an unfocused image of a lesion is used in a real-time diagnostic application, it might lead to a false diagnosis. So, a dual gradient analysis method was developed to successfully identify out-of-focus dermoscopy images. Also, robust lesion segmentation is required for better automatic melanoma identification. A Bayesian model was used to find the probabilities of skin in a given image after obtaining data from just 90 training images. Finally, the non-skin area is considered as the lesion, and post processing is done accordingly to obtain the lesion from the image. Finally, this method was tested on 1636 dermoscopy images to obtain the accuracy rates”--Abstract, page iv.


Moss, Randy Hays, 1953-

Committee Member(s)

Stoecker, William V.
Stanley, R. Joe
Shrestha, Bijaya


Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering


Missouri University of Science and Technology

Publication Date

Fall 2015

Journal article titles appearing in thesis/dissertation

  • Adaptable Ring for Vision-Based Measurements and Shape Analysis
  • Dual Gradient Analysis for a Vision-Based Focus Measurement in Digital Dermoscopy
  • Bayesian Approach for Automatic Lesion Segmentation and Border Detection in Automatic Melanoma Diagnosis


xi, 75 pages

Note about bibliography

Includes bibliographic references.


© 2015 Kanakam Teja Maddala, All rights reserved.

Document Type

Thesis - Open Access

File Type




Thesis Number

T 12035

Electronic OCLC #