Citrus black spot (CBS), or Guignardia citricarpa, is known as the most destroying citrus fungal disease worldwide. CBS causes yield loss as a result of early fruit drop, and it leaves severely blemished and unmarketable fruit. While leaves usually remain symptomless, CBS generates various forms of lesions on citrus fruits including hard spot, cracked spot, and virulent spot. CBS lesions often appear on maturing fruit, starting two months before maturity. Warm temperature and sunlight exposure increase the number of lesions. Two main sources of inoculum are infected leaves decomposing on citrus orchard floor and lesions on infected branches, fruits, and leaves. Wind and water splash can spread the disease to healthy trees. In order to better control the CBS disease, the infected trees should be identified and located preferably at the early stages of infection for an efficient site-specific treatment. In this paper, an affordable vision based sensing method was introduced that was able to detect the citrus fruit with CBS lesions under the field condition. It was shown in a previous study that CBS lesions could be identified with a 100% accuracy in a laboratory using only the color information in regular RGB images. Two DSLR cameras were modified to capture images in two NIR bands as well as red, green, and blue channels. Images of citrus trees were acquired in a grove near Immokalee, Florida, USA. An image analysis algorithm was developed to segment the potential spots on the citrus fruit and confirm if they are CBS lesions. Morphological features were extracted from the potential spots in all color components of the images. The algorithm was able to determine if a fruit is CBS positive or CBS negative. The results showed that acceptable accuracies using images that were obtained by the proposed sensing system. The proposed imaging method is an affordable diagnosis method for CBS detection under the field condition.