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Due to recent advances in visual neuroscience, the researchers tend to extend biologically plausible schemes to improve the accuracy of object recognition. Preprocessing is one part of the visual recognition system that has received much less attention. In this paper, we propose a new, simple, and biologically inspired pre processing technique by using the data\u2010driven mechanism of visual attention. In this part, the responses of Retinal Ganglion Cells (RGCs) are simulated. After obtaining these responses, an efficient threshold is selected. Then, the points of the raw image with the most information are extracted according to it. Then, the new images with these points are created, and finally, by combining these images with entropy coefficients, the most salient object is located. After extracting appropriate features, the classifier categorizes the initial image into one of the predefined object categories. Our system was evaluated on the Caltech\u2010101 dataset. Experimental results demonstrate the efficacy and effectiveness of this novel method of preprocessing.<\/jats:p>","DOI":"10.1155\/2021\/6699335","type":"journal-article","created":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T23:05:13Z","timestamp":1611961513000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Data\u2010Driven and Biologically Inspired Preprocessing Scheme to Improve Visual Object Recognition"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9005-9345","authenticated-orcid":false,"given":"Zahra Sadat","family":"Shariatmadar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1159-4866","authenticated-orcid":false,"given":"Karim","family":"Faez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,1,29]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"crossref","unstructured":"SerreT. 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