Is there opponent-orientation coding in the second-order channels of pattern vision?

نویسندگان

  • Norma Graham
  • S. Sabina Wolfson
چکیده

Is there opponency between orientation-selective processes in pattern perception, analogous to opponency between color mechanisms? Here we concentrate on possible opponency in second-order channels. We compare several possible second-order structures: SIGN-opponent-only channels in which there is no opponency between orientations (also called complex channels or filter-rectify-filter mechanisms); three structures we group under the name ORIENTATION-opponent; and finally BOTH-opponent channels which combine features of both SIGN-opponent-only and ORIENTATION-opponent channels but lead to predictions that are distinct from either of theirs. We measured observers' ability to segregate textures composed of checkerboard and striped arrangements of vertical and horizontal Gabor grating patches. The observers' performance was compared to model predictions from the alternative opponent structures. The experimental results are consistent with SIGN-opponent-only channels. The results rule out the ORIENTATION-opponent and BOTH-opponent structures. Further, when the models were expanded to include a contrast gain-control (inhibition among channels in a normalization network) the SIGN-opponent-only model was also able to explain a contrast-dependent effect we found, thus providing another piece of evidence that such normalization is an important process in human texture perception.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Different hue coding underlying figure segregation and region detection tasks.

Figure segregation from its background is one of the important functions of color vision for our visual system because it is a preliminary to shape recognition. However, little is known about the chromatic mechanisms underlying figure segregation as opposed to those underlying mere color discrimination and detection. We investigated whether there are differences in color difference thresholds b...

متن کامل

Orientation opponency in human vision revealed by energy-frequency analysis

Studies of second-order visual processing have primarily been concerned with understanding the mechanisms for detecting spatiotemporal variations in such attributes as contrast, orientation, spatial frequency, etc. Here, we have examined the orientation characteristics of second-order processes using bandpass noise whose Fourier energy is sinusoidally modulated across orientation, rather than a...

متن کامل

Second-order spatial frequency and orientation channels in human vision

We compared the number of spatial frequency and orientation mechanisms underlying first- versus second-order processing by measuring discrimination at detection threshold for first- and second-order Gabors to determine the smallest difference in spatial frequency and orientation that permits accurate discrimination at threshold. For second-order gratings, the number of channels is the same as f...

متن کامل

Orientation integration in detection and discrimination of contrast-modulated patterns

Orientation detection and discrimination thresholds were measured for Gabor 'envelopes' formed from contrast-modulation of luminance 'carriers'. Consistent with previous research differences between carrier and envelope orientation had no effect on sensitivity to envelopes. Using plaid carriers in which the proportion of contrast modulation 'carried' by each plaid component was systematically m...

متن کامل

Second-Order Statistical Texture Representation of Asphalt Pavement Distress Images Based on Local Binary Pattern in Spatial and Wavelet Domain

Assessment of pavement distresses is one of the important parts of pavement management systems to adopt the most effective road maintenance strategy. In the last decade, extensive studies have been done to develop automated systems for pavement distress processing based on machine vision techniques. One of the most important structural components of computer vision is the feature extraction met...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Vision Research

دوره 44  شماره 

صفحات  -

تاریخ انتشار 2004