Abstract
Haar cascade is a one of the popular machine learning algorithm used for object detection. The Haar algorithm identifies objects in image as well as video. The Haar algorithm was initially used to identify the body parts; later, it was used to for identifying any kind of object. The Haar identify the objects based on the features provided. The Haar algorithm is divided into four-part/stages: Haar feature selection, creating integral images, AdaBoost training, and cascading classifiers; the detailed analysis and implementation of all the four stages along with statistical data have been carried out in this paper, and also the process/step to be followed to create the Haar cascade file has been discussed in this paper. We can conclude that the Haar algorithm is more effective to recognize the object based on the features.
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Ghosh, G., Swarnalatha, K.S. (2022). A Detail Analysis and Implementation of Haar Cascade Classifier. In: Shetty D., P., Shetty, S. (eds) Recent Advances in Artificial Intelligence and Data Engineering. Advances in Intelligent Systems and Computing, vol 1386. Springer, Singapore. https://doi.org/10.1007/978-981-16-3342-3_28
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DOI: https://doi.org/10.1007/978-981-16-3342-3_28
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