The use of salient points in content-based retrieval allows an image index to represent local properties of the image. Classic corner detectors can also be used for this purpose but they have drawbacks when are applied to various natural images mainly because visual features do not need to be corners and corners may gather in small regions. In this paper, we present a salient point detector using wavelet transform and we compare it with two corner detectors using two criteria: repeatability rate and information content. We determine which detector gives the best results and show that it satisfies the criteria well.