Automatic Detection of Temples in consumer Images using histogram of Gradient
Madhav Singh Solanki, Laxmi Goswami, Kanta Prasad Sharma, Rishi Sikka · 2019
Automatic detection of Temples in consumer images is a very complex due to very less information to guess the variations in the testing sample. Object identification is a technically hard and practically useful problem in the field of computer vision. In this paper, we present a vision based system to recognize temples that considers a great deal of work has been done on vehicle, individual, bicycle and so forth. Hence, plan to work on temple detection that are included on our own dataset, Up to now no experimentation has been done on temple detection in image processing. According to computer vision point of view, temple detection is difficult because representation or shapes of various buildings are same. So we propose a novel approach to handle shape on temple detection using histogram of gradient. This approach mainly used in pedestrian detection and face detection by Navneet Dalal and Bill Triggs. Proposed work also includes those scenes which have same shape in temple and same in house detection. In the proposed work uses a model in which shape feature are taken to detect temple in images even when same shape is found in house.