Identification of Lines Based on Form Factor and Geometrical Descriptors

The problems of releasing and identifying features of key elements and their identification in images are shown. The basic algorithms and methods for forming descriptors for key elements in the image are considered. The main disadvantages of existing methods in aerospace images are the loss of stability and the presence of a large number of false key elements when changing recording to the conditions (for example, brightness and contrast of the received images). To eliminate these drawbacks, it is proposed to use selected lines as key elements, and their geometrical characteristics to form a descriptor. To analyze the proposed algorithm and the SIFT method, fragments of aerospace images changed in brightness and contrast in a graphic editor from -50 to +50 percent of the original were used, which made it possible to evaluate the operation of these algorithms in conditions close to the real survey. It is shown that the proposed algorithm is more stable than the SIFT method with increasing contrast and decreasing the brightness of the test aerospace image. Also, the proposed algorithm is characterized by a smaller number of detected false key elements compared to the SIFT method

Identification of Lines Based on Form Factor and Geometrical Descriptors

The problems of releasing and identifying features of key elements and their identification in images are shown. The basic algorithms and methods for forming descriptors for key elements in the image are considered. The main disadvantages of existing methods in aerospace images are the loss of stability and the presence of a large number of false key elements when changing recording to the conditions (for example, brightness and contrast of the received images). To eliminate these drawbacks, it is proposed to use selected lines as key elements, and their geometrical characteristics to form a descriptor. To analyze the proposed algorithm and the SIFT method, fragments of aerospace images changed in brightness and contrast in a graphic editor from -50 to +50 percent of the original were used, which made it possible to evaluate the operation of these algorithms in conditions close to the real survey. It is shown that the proposed algorithm is more stable than the SIFT method with increasing contrast and decreasing the brightness of the test aerospace image. Also, the proposed algorithm is characterized by a smaller number of detected false key elements compared to the SIFT method

Image Segmentation Approaches Applied for the Earth's Surface

An analytical review of papers about remote sensing, as well as semantic segmentation and classification methods to process these data, is carried out. Approaches such as template matching-based methods,machine learning and neural networks, as well as the application of knowledge about the analyzed objects are considered. The features of vegetation indices usage for data segmentation by satellite images are considered.Advantages and disadvantages are noted. Recommendations operations for a more accurate classification of thedetected areas on the sequence are give

Классификация методов сегментации снимков земной поверхности

В данной работе представлена классификация методов сегментации снимков земной поверхности. Рассмотрены такие подходы как сравнение с шаблоном, машинное обучение и глубокие нейронные сети, а также применение знаний об анализируемых объектах. Рассмотрены особенности применения вегетационных индексов для сегментации данных по спутниковым снимкам. Отмечены преимущества и недостатки. Систематизированы результаты, полученные авторами методик, появившихся за последние 10 лет, что позволит заинтересованным быстрее сориентироваться, сформировать идеи для последующих исследований