Proposed algorithm for image classification using regression-based pre-processing and recognition models
| Main Author: | Jittawiriyanukoon, Chanintorn |
|---|---|
| Format: | Article eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2019
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4065714 |
Daftar Isi:
- Image classification algorithms can categorize pixels regarding image attributes with the pre-processing of learner’s trained samples. The precision and classification accuracy are complex to compute due to the variable size of pixels (different image width and height) and numerous characteristics of image per se. This research proposes an image classification algorithm based on regression-based pre-processing and the recognition models. The proposed algorithm focuses on an optimization of pre-processing results such as accuracy and precision. To evaluate and validate, the recognition model is mapped in order to cluster the digital images which are developing the problem of a multidimensional state space. Simulation results show that compared to existing algorithms, the proposed method outperforms with the optimal amount of precision and accuracy in classification as well as results higher matching percentage based upon image analytics.