IDENTIFICATION OF VARIOUS DEFECTS IN PHARMACEUTICAL TABLETS USING IMAGE PROCESSING TECHNIQUES


Durga Karthik, Vijayarekha K, Saranya S

Abstract


 

 Objective: Our aim is to identify the damaged tablets from the manufacturing line using image processing techniques and remove them before packaging.

Methods: The various problems posed during inspection are broken tablets, corner chips, black or other color spots in tablets, empty blisters (without one or more tablets or capsules), foreign particles/color variation in the tablets/capsules, improper sealing, etc., Image processing techniques will be used for defect detection.

Results: Tablets are available in packed forms that are usually transparent, semi-transparent or opaque. Euclidean distance was employed for detecting defects, during testing that had a similarity of 100 for tablets with no defects, for defective blisters had similarity ranging from 98 to 41. Empty blisters had a similarity of 0 on comparing with trained images.

Conclusion: Similarity measuring based technique can accurately detect defects in the pharmaceutical tablets, hence can be adopted for removing such blisters from the manufacturing line itself.


Keywords


Tablet defects, Segmentation, Euclidean distance, Denoising, Edge detection.

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References


Sanket K, Garg SK. Fast dissolving tablets (FDTs): Current status, new market opportunities, recent advances in manufacturing technologies and future prospects. Int J Pharm Pharm Sci 2014;6(7):22-35.

Ketan S, Anuradha G, Jignasa S. Modified formulation of febuxostat: Improved efficacy and safety. Int J Pharm Pharm Sci 2015;8(1):359-366.

Manzoor M, Randhawa YS. Edge detection in digital image using statistical method. IOSR J Electron Commun Eng 2014;9(3):15-9.

Lakhani K, Minocha B, Gugnani N. Analyzing edge detection techniques for feature extraction in dental radiographs. Perspect Sci 2016;8:395-8.

Öztürk S, Akdemir B. Comparison of edge detection algorithms for texture analysis on glass production. Procedia Soc Behav Sci 2015;195:2675-82.

Lins RG, Givigi SN. Automatic crack detection and measurement based on image analysis. IEEE Trans Instrum Meas 2016;65(3):583-90.

Duarte A, Carrão L. Segmentation algorithms for thermal images. Procedia Technol 2014;16:1560-9.

Gnanasivam P, Muttan S. An efficient algorithm for fingerprint preprocessing and feature extraction Procedia Comput Sci 2010;2:133-42.

Jain S, Jagtap V, Pise N. Computer aided melanoma skin cancer detection using image processing. Procedia Comput Sci 2015;48:735-40.

Biswas S, Ghoshal D. Blood cell detection using thresholding estimation based watershed transformation with sobel filter in frequency domain. Procedia Comput Sci 2016;89:651-7.

Dimililer K, Ever YK, Ratemi H. Intelligent eye tumour detection system. Procedia Comput Sci 2016;102:325-32.

Karthik D, Vijayarekha K, Vinodha DA. Simple model for skin disease identification using image processing. Res J Pharm Biol Chem Sci 2016;7(4):2758-61.




About this article

Title

IDENTIFICATION OF VARIOUS DEFECTS IN PHARMACEUTICAL TABLETS USING IMAGE PROCESSING TECHNIQUES

Topics

Image processing

Keywords

Tablet defects, Segmentation, Euclidean distance, Denoising, Edge detection.

DOI

10.22159/ajpcr.2017.v10i11.20034

Date

01-11-2017

Additional Links

Manuscript Submission

Journal

Asian Journal of Pharmaceutical and Clinical Research
Vol 10 Issue 11 November 2017 Page: 106-108

Print ISSN

0974-2441

Online ISSN

2455-3891

Statistics

16 Views | 48 Downloads

Authors & Affiliations

Durga Karthik
Department of CSE, Sastra University, Thanjavur, Tamil Nadu, India
India

Vijayarekha K
Department of CSE, Sastra University, Thanjavur, Tamil Nadu, India
India

Saranya S
Department of CSE, Sastra University, Thanjavur, Tamil Nadu, India
India


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