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There is another way to solve the plant disease-detecting problem, which uses electromagnetic spectrum that is not in the visible range. It is an alternative way to detect the healthiness of plants. A healthy plant absorbs nearly all visible bands of the electromagnetic spectrum except it reflects about 10% of the green band because of chlorophyll absorption as shown in Fig. 3.19. This specific property of the plants is commonly used to differentiate between diseased and healthy plants.

Typically the differences in the reflectance between 550nm and 800nm can be used to discrimination of plants (Paap, Askraba, Alameh, & Rowe, 2008) from water and soil because electromagnetic reflectance are differs for plants in these specific wavelengths. The spectral image and reflectance of a plant are shown in Fig. 3.20.

Fig. 3.20. Spectral image and reflectance of a plant.

In order to discriminate the status of a plant it is possible to use a passive sensor in daylight conditions. Sun emission contains both Red and NIR bands that are shown in Fig. 3.21.

Fig. 3.21. Reflectance of plant, water and soil.

3.3.2 Multispectral Camera – Spektra TSL128RN

In this thesis, a custom-designed Multispectral Camera hardware and software designed and manufactured for detecting plant healthiness. The developed multispectral camera mounted on UGV as a disease-detecting sensor. It consists of line scanners, bandpass filters, varifocal lenses, laser modules, a microcontroller, a

Fig. 3.22. 3D model of the Multispectral Camera.

Table 3.4. Components of the Multispectral Camera.

Component Model Figure Description

Line scanner TSL1401CL 128X1 Linear

CCD Sensor 850nm Bandpass filter Optical Narrow Bandpass Filter 850NM Wavelength Bandpass Filter 660nm Bandpass filter Optical Narrow Bandpass Filter 660NM Wavelength Bandpass Filter

Lens Varifocal lens

3 Megapixel Fixed Iris M12 HD 2.8-12mm Varifocal Lens Wireless Transceiver DRF7020D27 GFSK transceiver Module -27dBm 433Mhz transparent RF module. Microcontroller At32MDB01 A custom designed development board is used for data acqusition.

USB interface FT232RL

FTDI

USB to serial UART Interface.

Laser module Line Laser

Module

Linear output

Laser Module.

3.3.3 The hardware of the Device

The main sensor module TSL1401CL is a linear sensor array consists of a 128 × 1 array of photodiodes, associated charge amplifier circuitry, and an internal pixel data-hold function that provides simultaneous-integration start and stop times

voltage for dark condition, Re is the device responsivity for a given wavelength of

light given in V/(μJ/cm2_{), E}

e is the incident irradiance in μW/cm2, tint is integration time in seconds.

The responsivity of the photodiode used in this line scanner sensor shown in Fig. 3.24 that indicates it is possible to sense both Red and NIR bands

Fig. 3.24. Photodiode spectral responsivity.

An MCU is used in this multispectral camera to obtain output of the line scanner sensors and transfer it to the GCS. In line with the purpose, an electronic development board designed and PCBs are printed. The schematic design of this microcontroller board is shown in Fig 3.25 and its PCB design is shown in 3.26. 3D

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 100 300 500 700 900 1100 1300 R e lati v e R e sp o n si v ity Wavelength (nm)

model of the board is shown in Fig 3.27 (a) and the manufacturing image is shown in Fig 3.27 (b).

Fig. 3.25. Schematic design of the board.

(a) (b)

Fig. 3.27. 3D Model of the board (a) and the Printed Circuit Board (PCB) (b).

3.3.4 Calibrating Steps of the Device

Field of View refers to the visual angle of a lens. Horizontal FoV (HFoV) describes horizontal dimensions and Vertical FoV (VFoV) describes vertical dimensions of the measurement field. For calculating the Field of View (FoV) of the Multispectral Camera, the relationship between the focal length of a camera and sensor size is investigated (Fig 3.28).

Fig. 3.28. Relationship between Focal Length, FoV and sensor size.

The FoV (α) can be calculated using trigonometry that is related to image plane dimension (ω) and focal length ( ƒ ) using the Eqn.(3.10) or (3.11).

𝛼 = 2 tan−1 𝜔 2𝑓 (3.10) or 𝑓 =𝜔 2cot 𝛼 2 (3.11)

Based on the above 3.11 using the image width ω, the field of view α and the focal length f can be calculated in pixels. This multispectral camera uses two separate lenses for two distinct bands. In order to eliminate non-coincident pixels for this camera a 3D model of FoV is simulated in computer modeling software as shown in Fig. 3.29 (a). Sensors of the multispectral camera are placed side by side and a target area is drawn to 1-meter distance from the sensors vertically. The angles of the sensors are for horizontal FoV and vertical FoV, 51.18 º and 30.04 º respectively as indicated in Fig. 3.29 (b).

(a) (b)

Fig. 3.29. The 3D model of sensor and sensing area relationship (a) and simulation of the FoV (b).

Total scanning FoV and the non-coincident area in 3D model of FoV are shown in Fig. 3.30 (a) and Fig. 3.30 (b), respectively.

(a) (b)

Fig. 3.30. Calculation of the intersecting area.

Horizontal and vertical FoVs of the sensors shown in Fig. 3.31.

(a) (b)

Fig. 3.31. FoV of the sensors, vertical FoV (a), horizontal FoV (b).

A simple 2D image demonstrated to explain intersection and difference to determine non-coincident pixels of sensors shown in Fig 3.32 for horizontal FoV.

The ratio between intersecting view and non-coincident view 𝑉𝑅 (3.12) is

𝑉𝑅 = 𝑉𝚤/𝑉𝑑 (3.12)

non-coincident pixel count 𝐶𝑝𝑖 (3.13),

𝐶𝑝𝑖=

𝐶𝑝

𝑉𝑅

(3.13)

intersecting pixel count 𝐶𝑝𝑖𝑖 is (3.14),

𝐶𝑝𝑖𝑖 = 𝐶𝑝−𝐶𝑝𝑖 (3.14)

where intersecting view 𝑉𝚤, non-coincident view (difference) 𝑉𝑑, the pixel count of

the sensor 𝐶𝑝, non-coincident pixel count 𝐶𝑝𝑖, intersecting pixel count 𝐶𝑝𝑖𝑖,

For 𝑉𝚤 = 34.17 mm, 𝑉𝑑 =1006.19 mm, 𝐶𝑝 = 128, 𝐶𝑝𝑖 is calculated 4.35 (~ 5) pixels

and 123 pixels are intersecting. For preventing from mounting and manufacturing errors 100 pixels Centered in Sensor are used and 14 pixels from left and right of the sensor are eliminated (3.15).

[1-14 not used, 14 -114 used, 114-128 not used] (3.1)

In order to calibrate the focal length of the multispectral camera lenses a CCTV camera is used (Fig 3.33). A target object is settled in front of the camera at 1-meter distance. Focal adjustment of the lenses is set manually by rotating lenses until the target image is clearly seen and then lenses are fixed.

Fig. 3.33. Focal Length Adjusting

In order to calibrate multispectral camera color printed calibration images (Fig. 3.34) and the relative spectral responsivity of the sensors are investigated. Calibration stage completed in the day time between 09:00-16:00. Varifocal lens focusing and zoom is adjustment accomplished using a CCTV camera shown in Fig. 3.33.

Fig. 3.34. Adjustment focal length and target object distance of Varifocal lenses.

3.3.5 Software for the Device

A desktop software interface is shown in Fig. 3.35 used for calibrating of the Multispectral Camera unit. In this calibration stage, an interface is coded in C++ language as desktop software. This interface shows each received pixel in real-time for Red and NIR bands. It calculates NDVI results using these two bands and offsets for calibrating the Multispectral Camera.

Fig. 3.35. Desktop Software for Calibration of Multispectral Camera.

In addition, another desktop software (Fig. 3.36) is coded for image acquisition from the Multispectral camera and is coded in the C++ language. This software shows real-time Simple Ratio (SR) with NDVI data and includes a scale to demonstrate the meaning of the results.

Fig. 3.37. Multispectral Camera assembly.

(a) (b)

Fig. 3.38. Multispectral camera units: electronic board and lenses (a), filters and laser module (b).