Digital Image Processing Techniques and Algorithms with MATLAB and SIMULINK
Digital image processing can be divided into three stages: acquisition, pre-processing, and feature extraction [ 3 ]. Each stage can be enhanced and improved according to the characteristics of the signal and the application of the system. This research presents a new a method based on digital image processing (DIP) for the characterization of seeds from thermal images. Thermal images are used to measure the external characteristics of agricultural products due to their high potential for use in precision agriculture [ 1 2 ]. However, the thermal images are affected by the characteristics of the light source and the environment. So, data annotation and image pre-processing are required to reduce noise and produce clearer images. The authors focus on grain surface temperature and seed age. The grain surface temperature reflects the hardness of seeds and the aspect and surface change of seeds during aging. As it is difficult to measure seeds during aging, the authors use the samples as seeds. In other words, the distribution of the surface temperature of the studied samples is assumed to be a temperature distribution of a seed. Thus, the researchers focus on the rate of grain temperature change and energy for the characterization of seeds. The temperature of a seed can be represented by the average of the average of temperature values [ 3 ].
Procesamiento digital de imagenes con matlab y simulink pdf
Digital images are produced by a process of converting information on a screen or other device to digital form [ 1 ]. These information can be continuous or discrete. Digital images can be considered as continuous if the image information varies in a certain interval of gray level, and discrete if it is binary.