Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems

Abstract

The application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI) for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR) and the red channel optical frequency band. Two aligned charge coupled device (CCD) chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed.

Precise Navigation of Small Agricultural Robots in Sensitive Areas with a Smart Plant Camera

“…For low-quality images from Scenes 6 to 9, the binary results differ from the gray-scale results. Therefore, the faster binary approach requires an adequate camera mounting and good plant camera system with efficient binary results independent of lighting [18]. The first scene shows an orthogonal tracking line, for which the R 2 value is useless for typical straight driving directions; as a result, the RMSE value should be used as the quality indicator.…”

“…The IR-cutoff filter must be removed, and a low-pass filter from approximately 645 nm to 950 nm (RG645, SCHOTT AG, 55122 Mainz, Germany) should be used. Better results can be achieved with an adapted double band-pass filter [18], although this configuration has a higher cost. An adequate CMOS chip is the Aptina MT9V032STC (Aptina Imaging Corporation, San Jose, CA, USA), which has high NIR sensitivity at 850 nm ( Figure 2) and provides an image with 752 × 480 pixels.…”

“…These algorithms are usually optimized for RGB images and do not operate properly for new channel configurations. With optimized NDVI images, enhanced binary images can be produced [18], and they simplify the subsequent image processing applications [20].…”

“…An adequate CMOS chip is the Aptina MT9V032STC (Aptina Imaging Corporation, San Jose, CA, USA), which has high NIR sensitivity at 850 nm ( Figure 2) and provides an image with 752 × 480 pixels. [18]. Figure 2 shows the usable spectral range of the camera chip after implementing an optical filter.…”

“…Several optimizations can be used improve the contrast between plants and soil in the images [18], but the most important are debayering control and white balancing termination in custom cameras. These algorithms are usually optimized for RGB images and do not operate properly for new channel configurations.…”