<![CDATA[Lobster in Indonesia consists of various types of colors, shapes, and habitats. Documentation results from several studies in the field of fisheries show the dynamics and richness of this type of shrimp species that have a hard and large skeleton. It is necessary to apply this knowledge to the field of information technology and computerization. The application that is right on target for the community is the application that is felt to be useful in the activities of the community itself. The application of information on lobster diversity found in Indonesia in the form of computer technology is to create a knowledge-based lobster recognition computer. This computer technology is designed as a computer vision identification of species, sex, and age of Indonesian water lobsters. Lobster identification is built with three levels of structure, namely the introduction of the type of lobster, the introduction of the sex of the lobster, and the introduction of the age of the lobster. The identification of lobster species here uses color recognition and edge detection techniques from lobster body image data that has been stored in a python-based value library file. For gender recognition using edge detection and pattern recognition techniques from image data of the bottom of the lobster such as the image of the legs. Meanwhile, for the introduction of lobster age, the technique of measuring the length of the lobster carapace distance was used. All these objects can be identified by the features provided by OpenCV in Python language]]>
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