Ramp edges, Mach bands, and the functional significance of the simple cell assembly

Abstract

Abstract. The responses of "complex" simple cells to sharp and blurred ramp edges were studied. These responses are quite similar to those in the case of lines, which implies that phase information cannot be used to discriminate between ramp edges and lines. Furthermore, if the maximum of the modulus is used as a position estimate, a systematic bias toward the ramp side results, and this bias increases with edge blur. In contrast, a local extremum in the real part of the cell responses provides a precise position estimate, even for strongly blurred edges. Possible multiscale detection strategies are discussed in the context of a syntactical visual reconstruction. This is illustrated by an explanation of Mach bands as perceived at trapezoidal edges, including Ratlitt's Mach-band cancellation stimulus, and criteria for local probability summation in the prediction of Mach-band detection thresholds are presented.

Energy Feature Integration for Motion Segmentation

“…PC is the measure of the local degree of alignment of the local phase of Fourier components of a signal. The sensitivity of the HVS to PC has also been Vision Systems -Segmentation and Pattern Recognition 4 studied by other authors (Fleet, 1992;Oppenheim & Lim, 1981;Ross et al, 1989;du Buf, 1994). As demonstrated by Venkatesh and Owens (1990), points whose PC is locally maximal coincide with the locations of energy maxima.…”

Multi-scale lines and edges in V1 and beyond: Brightness, object categorization and recognition, and consciousness

“…As for image coding, this representation must be complemented with a lowpass filter, a process that may exist by means of retinal ganglion cells with big photoreceptive dendritic fields not (in)directly connected to rods and cones, the main photoreceptors (Berson, 2003). One brightness model (du Buf, 1994;du Buf and Fischer, 1995) is based on the symbolic line and edge interpretation. It explains Mach bands (Pessoa, 1996) by the fact that responses of simple cells cannot discriminate lines from ramp edges, and it was shown to be able to predict many brightness illusions such as simultaneous brightness contrast and assimilation, which are two opposite induction effects (the model referred to above was first tested in 1D and has now been extended to 2D).…”

Face Recognition by Cortical Multi-scale Line and Edge Representations

“…One brightness model [5] is based on the symbolic line/edge interpretation referred to above. It is one of the very few models that can explain Mach bands [6,16].…”