To enhance the efficiency of machine vision system, physical hardware capable of sensing and encoding is essential. However, sensing and encoding color information has been overlooked. Therefore, this work utilizes an indium-gallium-zinc oxide (IGZO) phototransistor to detect varying densities of red, green, and blue (RGB) light, converting them into corresponding drain current (I_D) states. By applying stochastic gate voltage (V_G) pulses to the IGZO phototransistor, the fluctuations are generated in these I_D states. When the I_D exceeds the threshold current (I_TC), a spike signal is generated. This approach enables the conversion of light densities into spike signals, achieving spike-rate encoding. Moreover, adjusting the standard deviation (σ) of the V_G pulses controls the range of light densities converted into spike rates, while altering the mean (μ) of the V_G pulses changes the baseline level of spike rates. Remarkably, separate RGB channels offer a tunable encoding process, which can emphasize individual colors and correct color bias. The encoded spike rates are also fed into a spiking neural network (SNN) for CIFAR-10 pattern recognition, achieving an accuracy of 86%. The method allows the operation of SNN and shows the tunability in the process of light-to-spike encoding, opening possibilities for color image processing.