Feature extraction of shrimp with computer vision /
| Main Author: | |
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| Other Authors: | , |
| Format: | Thesis Book |
| Language: | English |
| Published: |
1989.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Abstract: | Features were identified and evaluated for a machine vision based shrimp deheader. The two major steps in the extraction process were (1) feature identification and (2) feature retrieval. Spectral and morphological features were examined for fast head identification of the shrimp, Penaeus vannamei. Spectral features included transmittance, reflectance, and emittance of the shrimp. Reflectance and transmittance were evaluated between 400 and 1000 nm. Morphological features included five morphometric variable measurements provided by biologists and a new feature that was generated by a thinning operation on the shrimp images. The features were retrieved with machine vision techniques. Major tasks in spectral feature retrieval were the design and evaluation of (1) adaptive thresholding techniques, (2) classifiers, and (3) scanning algorithms to locate the cutting reference point for the deheading process. The intensity averaging thresholding technique was developed to determine threshold values adaptively for color varying shrimp. This technique was effective and fast in segmenting shrimp images. The recognition operation was accomplished with a two step procedure: (1) identification of the hepato pancreas (HP) and (2) location of the cutting reference point. Two simple classifiers were evaluated to classify the HP blob from video noise in the shrimp images. A scanning algorithm based on the medial axis transform (MAT) concept was developed for faster labeling of the cutting reference point.. |
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| Item Description: | Typescript (photocopy). Vita. "Major subject: Mechanical engineering." |
| Physical Description: | xviii, 136 leaves : illustrations ; 29 cm |
| Bibliography: | Includes bibliographical references. |