# A Study of Image Pre-processing for Faster Object Recognition

arXiv: https://arxiv.org/abs/2011.06928 · HTML: https://mlsanity.com/paper/2011.06928/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2020.

## Built on by (most cited first, 2 of 2)

- [Inhomogeneous illumination image enhancement under ex-tremely low visibility condition](https://mlsanity.com/paper/2404.17503/) (2024)
- [Input Resolution Matters: Real-Time Object Detection Latency](https://mlsanity.com/paper/2609.12920/) (2026)

## Abstract (arXiv)

Quality of image always plays a vital role in in-creasing object recognition or classification rate. A good quality image gives better recognition or classification rate than any unprocessed noisy images. It is more difficult to extract features from such unprocessed images which in-turn reduces object recognition or classification rate. To overcome problems occurred due to low quality image, typically pre-processing is done before extracting features from the image. Our project proposes an image pre-processing method, so that the performance of selected Machine Learning algorithms or Deep Learning algorithms increases in terms of increased accuracy or reduced the number of training images. In the later part, we compare the performance results by using our method with the previous used approaches.