
Pest detection is crucial to secure crops and ensure food quality. A lot of work is being carried out for the effective identification of pests. In this paper we will develop a novel and fast methodology to detect and enumerate the pests present in an image using rapid feature detection algorithm. The amount of pesticides being used for agriculture pollutes the environment, with sophisticated machine vision systems that implement this algorithm we can make machines that utilize pesticides effectively by selective targeting pests using image processing. In the current scenario, human labor is used for the manual detection of pests which is not highly accurate. Automation is required in this field as it would be accurate in the detection of pests in crops. This paper proposes a system that would automate the detection of pests in crops using digital image processing techniques.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
