opencv-python object detection
Your question is way too general. Feature matching is a very vast field.
The type of algorithm to be used totally depends on the object you want to detect, its environment etc.
So if your object won't change its size or angle in the image then use Template Matching.
If the image will change its size and orientation you can use SIFT or SURF.
If your object has unique color features that is different from its background, you can use hsv method.
If you have to classify a group of images as you object,for example all the cricket bats should be detected then you can train a number of positive images to tell the computer how the object looks like and negative image to tell how it doesn't, it can be done using haar training.
I'm a beginner in opencv using python. I have many 16 bit gray scale images and need to detect the same object every time in the different images. Tried template matching in opencv python but needed to take different templates for different images which could be not desirable. Can any one suggest me any algorithm in python to do it efficiently.