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Object detection is important task in image processing and computer vision. To identify objects in images or pictures, objects have various features. Objects have various features in the form of feature vectors. Feature vector are being extracted for the object detection. There are ways for detection objects that are texture, colour and shape. Texture is the surface of the object. Texture based object detection is further divided in sub types texture segmentation, region based, edge based. In order to shape is most stable and explanative way for object detection. Further shape is divided in two subtypes region based and contour based. In this contour based is more used because these methods are invariant to rotation scaling and transposition invariant of the object. All the ways and its subtypes are discussed in this paper. Object detection is being used in many applications robot navigation, augmented reality, CBIR.
[1] Supriya A.Waghmare, Prof. Sheetal Thakare, “Object Detection Strategies: Survey,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2018.7715
